Modelling coffee leaf rust risk in Colombia with climate reanalysis data

Weather-Based Logistic Regression Models for Predicting Wheat Head Blast Epidemics

Wheat head blast is a major disease of wheat in the Brazilian Cerrado. Empirical models for predicting epidemics were developed using data from field trials conducted in Patos de Minas (2013 to 2019) and trials conducted across 10 other sites (2012 to 2020) in Brazil, resulting in 143 epidemics, with each being classified as either outbreak (≥20% head blast incidence) or nonoutbreak. Daily weather variables were collected from the National Aeronautics and Space Administration (NASA) Prediction of Worldwide Energy Resources (POWER) website and summarized for each epidemic. Wheat heading date (WHD) served to define four time windows, with each comprising two 7-day intervals (before and after WHD), which combined with weather-based variables resulted in 36 predictors (nine weather variables × four windows). Logistic regression models were fitted to binary data, with variable selection using least absolute shrinkage and selection operator (LASSO) and sequentially best subset analyses. The models were validated using the leave-one-out cross-validation (LOOCV) technique, and their statistical performance was compared. One model was selected, implemented in a 24-year series, and assessed by experts and literature. Models with two to five predictors showed accuracies between 0.80 and 0.85, sensitivities from 0.80 to 0.91, specificities from 0.72 to 0.86, and area under the curve (AUC) from 0.89 to 0.91. The accuracy of LOOCV ranged from 0.76 to 0.81. The model applied to a historical series included temperature and relative humidity in preheading date, as well as postheading precipitation. The model accurately predicted the occurrence of outbreaks, aligning closely with real-world observations, specifically tailored for locations with tropical and subtropical climates.

Diversity of Leaf Fungal Endophytes from Two Coffea arabica Varieties and Antagonism towards Coffee Leaf Rust

Coffee has immense value as a worldwide-appreciated commodity. However, its production faces the effects of climate change and the spread of severe diseases such as coffee leaf rust (CLR). The exploration of fungal endophytes associated with Coffea sp. has already found the existence of nearly 600 fungal species, but their role in the plants remains practically unknown. We have researched the diversity of leaf fungal endophytes in two Coffea arabica varieties: one susceptible and one resistant to CLR. Then, we conducted cross-infection essays with four common endophyte species (three Colletotrichum sp. and Xylaria sp. 1) and Hemileia vastatrix (CLR) in leaf discs, to investigate the interaction of the endophytes on CLR colonisation success and severity of infection. Two Colletotrichum sp., when inoculated 72 h before H. vastatrix, prevented the colonisation of the leaf disc by the latter. Moreover, the presence of endophytes prior to the arrival of H. vastatrix ameliorated the severity of CLR. Our work highlights both the importance of characterising the hidden biodiversity of endophytes and investigating their potential roles in the plant-endophyte interaction.

Impact of ontogenic changes on the dynamics of a fungal crop disease model motivated by coffee leaf rust

Ontogenic resistance has been described for many plant-pathogen systems. Conversely, coffee leaf rust, a major fungal disease that drastically reduces coffee production, exhibits a form of ontogenic susceptibility, with a higher infection risk for mature leaves. To take into account stage-dependent crop response to phytopathogenic fungi, we developed an SEIR-U epidemiological model, where U stands for spores, which differentiates between young and mature leaves. Based on this model, we also explored the impact of ontogenic resistance on the sporulation rate. We computed the basic reproduction number [Formula: see text], which classically determines the stability of the disease-free equilibrium. We identified forward and backward bifurcation cases. The backward bifurcation is generated by the high sporulation of young leaves compared to mature ones. In this case, when the basic reproduction number is less than one, the disease can persist. These results provide useful insights on the disease dynamics and its control. In particular, ontogenic resistance may require higher control efforts to eradicate the disease.

Impulsive modelling of rust dynamics and predator releases for biocontrol

Fungal diseases cause serious damages in crop worldwide. In particular, coffee leaf rust (CLR), caused by fungus Hemileia vastatrix attacks coffee leaves and reduces coffee yield. This paper presents a multi-seasonal model of the CLR development in the coffee plantation with continuous dynamics during the rainy season and a discrete event to represent the simpler dynamics during the dry season. Biological control using predators through one or more discrete introduction events over the year is then added. Analytical and semi-numerical studies are performed to identify how much and how frequently predators need to be introduced through the definition of a threshold value, as a function of various parameters. We show that the best strategy to efficiently control the disease depends on the predator mortality: low mortality parasites need be released only once a year, while high mortality parasites should be released more frequently to ensure their persistence in the plantation. This work hence provides qualitative and quantitative bases for the deployment of predator-based biocontrol, a promising alternative to fungicides for rust control.

A Systematic Review on the Impacts of Climate Change on Coffee Agrosystems

Coffee production is fragile, and the Intergovernmental Panel on Climate Change (IPCC) reports indicate that climate change (CC) will reduce worldwide yields on average and decrease coffee-suitable land by 2050. This article adopted the systematic review approach to provide an update of the literature available on the impacts of climate change on coffee production and other ecosystem services following the framework proposed by the Millenium Ecosystem Assessment. The review identified 148 records from literature considering the effects of climate change and climate variability on coffee production, covering countries mostly from three continents (America, Africa, and Asia). The current literature evaluates and analyses various climate change impacts on single services using qualitative and quantitative methodologies. Impacts have been classified and described according to different impact groups. However, available research products lacked important analytical functions on the precise relationships between the potential risks of CC on coffee farming systems and associated ecosystem services. Consequently, the manuscript recommends further work on ecosystem services and their interrelation to assess the impacts of climate change on coffee following the ecosystem services framework.

Global predictions for the risk of establishment of Pierce's disease of grapevines

The vector-borne bacterium Xylella fastidiosa is responsible for Pierce's disease (PD), a lethal grapevine disease that originated in the Americas. The international plant trade is expanding the geographic range of this pathogen, posing a new threat to viticulture worldwide. To assess the potential incidence of PD, we have built a dynamic epidemiological model based on the response of 36 grapevine varieties to the pathogen in inoculation assays and on the vectors' distribution when this information is available. Key temperature-driven epidemiological processes, such as PD symptom development and recovery, are mechanistically modelled. Integrating into the model high-resolution spatiotemporal climatic data from 1981 onward and different infectivity (R0) scenarios, we show how the main wine-producing areas thrive mostly in non-risk, transient, or epidemic-risk zones with potentially low growth rates in PD incidence. Epidemic-risk zones with moderate to high growth rates are currently marginal outside the US. However, a global expansion of epidemic-risk zones coupled with small increments in the disease growth rate is projected for 2050. Our study globally downscales the risk of PD establishment while highlighting the importance of considering climate variability, vector distribution, and an invasive criterion as factors to obtain better PD risk maps.

Variable climate suitability for wheat blast (Magnaporthe oryzae pathotype Triticum) in Asia: results from a continental-scale modeling approach

Crop fungal diseases constitute a major cause of yield loss. The development of crop disease monitoring and forecasting tools is an important effort to aid farmers in adapting to climate variability and change. Recognizing weather as a main driver of fungal disease outbreaks, this work assesses the climate suitability for wheat blast (Magnaporthe oryzae pathotype Triticum, MoT) development in Asian wheat-producing countries. MOT was reported for the first time in Bangladesh in 2016 and could spread to other countries, provided that environmental conditions are suitable to spore development, distribution, and infection. With results from a generic infection model driven by air temperature and humidity, and motivated by the necessity to assess the potential distribution of MoT based on the response to weather drivers only, we quantify potential MOT infection events across Asia for the period 1980-2019. The results show a potential higher incidence of MOT in Bangladesh, Myanmar, and some areas of India, where the number of potential infection (NPI) events averaged up to 15 during wheat heading. Interannual trends show an increase in NPI over those three countries, which in turns show their higher interannual variability. Cold/dry conditions in countries such as Afghanistan and Pakistan appear to render them unlikely candidates for MOT establishment. The relationship between seasonal climate anomalies and NPI suggests a greater association with relative humidity than with temperature. These results could help to focus future efforts to develop management strategies where weather conditions are conducive for the establishment of MOT.

Risk Assessment of Ozone Fumigation Under Vacuum to Control Potential Infestation of Coffee Berry Borer and Coffee Leaf Rust in Green Coffee Beans Imported Into Hawaii

Studies were conducted with ozone gas fumigation under vacuum as a methyl bromide alternative against life stages of coffee berry borer (CBB) Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae: Scolytinae), and the urediniospores of coffee leaf rust (CLR), Hemileia vastatrix Berkeley & Broome (Basidiomycota: Pucciniales) in green coffee, Coffea spp. L. Fumigation with 10,000 ppm O3 gas under -25.4 mm Hg vacuum1 at 13.0 ± 3.0°C for 6.0 h killed all CBB larvae, pupae, and adults, but did not kill all CBB eggs (~15% survival). Mortality of CLR urediniospores was 100% within the first hour of the 6-h fumigation. Ozone fumigation had no adverse effects on coffee quality. Results indicated that CBB adult hitchhikers may be the only target life stage of quarantine concern, and additional studies focused on this stage. CBB adult survival and reproduction decreased significantly at moisture contents ≤20%, and F1 generation survival did not occur in green coffee at moisture contents ≤15%. As the international standard for green coffee moisture content is 9-12%, adult CBB should not survive or reproduce in exported dry green coffee. Standard industry processing of harvested coffee cherries to the green coffee stage using either mechanical- or sun-drying eliminated CBB infestations from the field. A systems approach is recommended for exporting green coffee to control CBB and CLR that includes eliminating CBB life stages with standard processing methods, reducing moisture content to 9-12% to prevent egg deposition, survival or reproduction, and O3 fumigation to ensure quarantine security against potential CBB adult hitchhikers.

Use of meteorological data in biosecurity

Pests, pathogens and diseases cause some of the most widespread and damaging impacts worldwide — threatening lives and leading to severe disruption to economic, environmental and social systems. The overarching goal of biosecurity is to protect the health and security of plants and animals (including humans) and the wider environment from these threats. As nearly all living organisms and biological systems are sensitive to weather and climate, meteorological, ‘met’, data are used extensively in biosecurity. Typical applications include, (i) bioclimatic modelling to understand and predict organism distributions and responses, (ii) risk assessment to estimate the probability of events and horizon scan for future potential risks, and (iii) early warning systems to support outbreak management. Given the vast array of available met data types and sources, selecting which data is most effective for each of these applications can be challenging. Here we provide an overview of the different types of met data available and highlight their use in a wide range of biosecurity studies and applications. We argue that there are many synergies between meteorology and biosecurity, and these provide opportunities for more widespread integration and collaboration across the disciplines. To help communicate typical uses of meteorological data in biosecurity to a wide audience we have designed the ‘Meteorology for biosecurity’ infographic.

Epidemics and the future of coffee production

In this perspective, we draw on recent scientific research on the coffee leaf rust (CLR) epidemic that severely impacted several countries across Latin America and the Caribbean over the last decade, to explore how the socioeconomic impacts from COVID-19 could lead to the reemergence of another rust epidemic. We describe how past CLR outbreaks have been linked to reduced crop care and investment in coffee farms, as evidenced in the years following the 2008 global financial crisis. We discuss relationships between CLR incidence, farmer-scale agricultural practices, and economic signals transferred through global and local effects. We contextualize how current COVID-19 impacts on labor, unemployment, stay-at-home orders, and international border policies could affect farmer investments in coffee plants and in turn create conditions favorable for future shocks. We conclude by arguing that COVID-19's socioeconomic disruptions are likely to drive the coffee industry into another severe production crisis. While this argument illustrates the vulnerabilities that come from a globalized coffee system, it also highlights the necessity of ensuring the well-being of all. By increasing investments in coffee institutions and paying smallholders more, we can create a fairer and healthier system that is more resilient to future social-ecological shocks.

New Varieties of Coffee: Compromising the Qualities of Adaptive Agroforestry? A Case Study From Southern Mexico

The most recent wave of coffee leaf rust, and its interaction with climatic variability, caused severe crop losses in shade-grown coffee areas in Latin America during the 2010–14 production cycles and beyond. Fungal attack on traditional Arabica varieties led to a process of substitution with new coffee varieties that are tolerant or resistant to the pathogen. The adaptation literature classifies this type of intervention as an incremental adaptation, with the potential to lead the system toward sustainable transformation. This research explores the initial consequences of introducing certain hybrid varieties into the transboundary area of the Tacaná Volcano, located between Chiapas and Guatemala, with the objective of identifying aspects that put the potential for adaptive agroforestry at risk. We hypothesize that the interaction of a range of economic, political, and ecological factors leads to ambiguous results in terms of both production and environmental adaptation. Ecological and management variables were analyzed in a case study of 30 producers. Quantitative data, collected through ecological plot sampling and application of a socio-productive survey, was complemented with ethnographic data. We conclude that, for our case study, the manner in which these new coffee varieties were introduced raises new sources of vulnerability that could be compromising the local and ecological benefits of agroforestry systems, as well as diminishing their capacity to cope with the future impacts of climate change.

Hybrid coffee cultivars may enhance agroecosystem resilience to climate change

Anthropogenic climate change is predicted to cause shifts in temperature and precipitation patterns that will be detrimental for global agriculture. Developing comprehensive strategies for building climate resilient agroecosystems is critical for maintaining future crop production. Arabica coffee (Coffea arabica) is highly sensitive to the quantity and timing of precipitation, so alterations in precipitation patterns that are predicted under climate change are likely to be a major challenge for maintaining coffee agroecosystems. We assessed cultivar selection as a potential component of more resilient coffee agroecosystems by evaluating water stress responses among five Arabica coffee cultivars (clonal hybrids H10 and H1 and seedling lines Catuai 44, Catuai, and Villa Sarchi) using a precipitation reduction experiment in the highlands of Tarrazú, Costa Rica. During the first harvest (eighteen months after planting), plants under the rainout treatment had 211 % greater total fruit weight and over 50 % greater biomass than under the control treatment, potentially due to protection from unusually high rainfall during this period of our experiment. At the second harvest (30 months after planting), after a year of more typical rainfall, plants under rainout still produced 66 % more fruit by weight than under control. The magnitude of the responses varied among cultivars where, at the first harvest, H10 and H1 had approximately 92 % and 81 % greater fruit production and 18 % and 22 % greater biomass, respectively, and at the second harvest H10 had 60 % more fruit production than the overall average. Thus, our findings suggest that the hybrid lines H10 and H1 are more resilient than the other cultivars to the stress of high soil moisture. Overall, our results indicate that stress due to higher than average rainfall could impair coffee plant growth and production, and that cultivar selection is likely to be an important tool for maintaining the viability of coffee production, and the resilience of global agroecosystems more generally, under climate change.

Impact of climate change and early development of coffee rust - An overview of control strategies to preserve organic cultivars in Mexico

Coffee is one of the most important commercial traded commodities in the international market, as well as the most popular beverage around the world. In Mexico, organic coffee cultivation (specifically, Arabica coffee crops) is a highly demanded that generates up to 500,000 employments in 14 federal entities. Among various coffee producers, Chiapas, Veracruz, and Oaxaca are responsible of 80% of the total coffee production in the country. Currently, Mexico is the leading producer of organic coffee in the world. However, there have been a slow recovery due to the large production losses since 2012, caused by earlier and highly aggressive outbreaks of coffee leaf rust (CLR), in the country, where the infectious agent is known as Hemileia vastatrix (HV). This phenomenon is becoming frequent, and climate change effects could be the main contributors. This spontaneous proliferation was generated in Mexico, due to the precipitation and temperature variability, during the last decade. As result, in Mexico, the biological interaction between coffee crops and their environment has been harmed and crucial characteristics, as crop yield and quality, are particularly being affected, directly by the negative effects of the greenhouse phenomenon, and indirectly, through diseases as CLR. Therefore, this review discusses the contribution of climate change effects in the early development of CLR in Mexico. The focus is also given on possible schemes and actions taken around the world as control measures to adapt the vulnerable coffee varieties to tackle this challenging issue.

Threats to global food security from emerging fungal and oomycete crop pathogens

Emerging fungal and oomycete pathogens infect staple calorie crops and economically important commodity crops, thereby posing a significant risk to global food security. Our current agricultural systems - with emphasis on intensive monoculture practices - and globalized markets drive the emergence and spread of new pathogens and problematic traits, such as fungicide resistance. Climate change further promotes the emergence of pathogens on new crops and in new places. Here we review the factors affecting the introduction and spread of pathogens and current disease control strategies, illustrating these with the historic example of the Irish potato famine and contemporary examples of soybean rust, wheat blast and blotch, banana wilt and cassava root rot. Our Review looks to the future, summarizing what we see as the main challenges and knowledge gaps, and highlighting the direction that research must take to face the challenge of emerging crop pathogens.

Climate change effects on Black Sigatoka disease of banana

Climate change has significantly altered species distributions in the wild and has the potential to affect the interactions between pests and diseases and their human, animal and plant hosts. While several studies have projected changes in disease distributions in the future, responses to historical climate change are poorly understood. Such analyses are required to dissect the relative contributions of climate change, host availability and dispersal to the emergence of pests and diseases. Here, we model the influence of climate change on the most damaging disease of a major tropical food plant, Black Sigatoka disease of banana. Black Sigatoka emerged from Asia in the late twentieth Century and has recently completed its invasion of Latin American and Caribbean banana-growing areas. We parametrize an infection model with published experimental data and drive the model with hourly microclimate data from a global climate reanalysis dataset. We define infection risk as the sum of the number of modelled hourly spore cohorts that infect a leaf over a time interval. The model shows that infection risk has increased by a median of 44.2% across banana-growing areas of Latin America and the Caribbean since the 1960s, due to increasing canopy wetness and improving temperature conditions for the pathogen. Thus, while increasing banana production and global trade have probably facilitated Black Sigatoka establishment and spread, climate change has made the region increasingly conducive for plant infection.

This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.

Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants

The 1918 influenza pandemic is one of the most devastating infectious disease epidemics on record, having caused approximately 50 million deaths worldwide. Control measures, including prohibiting non-essential gatherings as well as closing cinemas and music halls, were applied with varying success and limited knowledge of transmission dynamics. One hundred years later, following developments in the field of mathematical epidemiology, models are increasingly used to guide decision-making and devise appropriate interventions that mitigate the impacts of epidemics. Epidemiological models have been used as decision-making tools during outbreaks in human, animal and plant populations. However, as the subject has developed, human, animal and plant disease modelling have diverged. Approaches have been developed independently for pathogens of each host type, often despite similarities between the models used in these complementary fields. With the increased importance of a One Health approach that unifies human, animal and plant health, we argue that more inter-disciplinary collaboration would enhance each of the related disciplines. This pair of theme issues presents research articles written by human, animal and plant disease modellers. In this introductory article, we compare the questions pertinent to, and approaches used by, epidemiological modellers of human, animal and plant pathogens, and summarize the articles in these theme issues. We encourage future collaboration that transcends disciplinary boundaries and links the closely related areas of human, animal and plant disease epidemic modelling. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

Expecting the unexpected: factors influencing the emergence of fungal and oomycete plant pathogens

In recent years, the number of emergent plant pathogens (EPPs) has grown substantially, threatening agroecosystem stability and native biodiversity. Contributing factors include, among others, shifts in biogeography, with EPP spread facilitated by the global unification of monocultures in modern agriculture, high volumes of trade in plants and plant products and an increase in sexual recombination within pathogen populations. The unpredictable nature of EPPs as they move into new territories is a situation that has led to sudden and widespread epidemics. Understanding the underlying causes of pathogen emergence is key to managing the impact of EPPs. Here, we review some factors specifically influencing the emergence of oomycete and fungal EPPs, including new introductions through anthropogenic movement, natural dispersal and weather events, as well as genetic factors linked to shifts in host range.

Coffee, Migration and Climatic Changes: Challenging Adaptation Dichotomic Narratives in a Transborder Region

The narratives of migration as adaptation and in situ adaptation are well established in mainstream adaptation policy and are usually presented as independent and opposing trends of action. A common and fundamental element of such narratives is the depoliticized conception of both migration and adaptation. Using a trans-scalar approach, we address the migration–coffee–climate change nexus: first at a regional scale, at the conflictive border of Guatemala–Mexico, to show the contradiction between the current Central American migratory crisis and the narrative of migration as adaptation; second, at a local scale and from an ethnographic perspective, we focus on the process of in situ adaptation in shade-grown coffee plots of smallholder coffee farmers in the Tacaná Volcano cross-border region, between Chiapas and Guatemala. We argue that the dichotomy “in situ adaptation” versus “migration as adaptation” is not useful to capture the intertwined and political nature of both narratives, as illustrated in the case of the renovation of smallholders’ coffee plots in a context of climatic changes. We provide elements to contribute towards the repolitization of adaptation from an integral perspective.

Many unreported crop pests and pathogens are probably already present

Invasive species threaten global biodiversity, food security and ecosystem function. Such incursions present challenges to agriculture where invasive species cause significant crop damage and require major economic investment to control production losses. Pest risk analysis (PRA) is key to prioritize agricultural biosecurity efforts, but is hampered by incomplete knowledge of current crop pest and pathogen distributions. Here, we develop predictive models of current pest distributions and test these models using new observations at subnational resolution. We apply generalized linear models (GLM) to estimate presence probabilities for 1,739 crop pests in the CABI pest distribution database. We test model predictions for 100 unobserved pest occurrences in the People's Republic of China (PRC), against observations of these pests abstracted from the Chinese literature. This resource has hitherto been omitted from databases on global pest distributions. Finally, we predict occurrences of all unobserved pests globally. Presence probability increases with host presence, presence in neighbouring regions, per capita GDP and global prevalence. Presence probability decreases with mean distance from coast and known host number per pest. The models are good predictors of pest presence in provinces of the PRC, with area under the ROC curve (AUC) values of 0.75-0.76. Large numbers of currently unobserved, but probably present pests (defined here as unreported pests with a predicted presence probability >0.75), are predicted in China, India, southern Brazil and some countries of the former USSR. We show that GLMs can predict presences of pseudoabsent pests at subnational resolution. The Chinese literature has been largely inaccessible to Western academia but contains important information that can support PRA. Prior studies have often assumed that unreported pests in a global distribution database represent a true absence. Our analysis provides a method for quantifying pseudoabsences to enable improved PRA and species distribution modelling.

Many unreported crop pests and pathogens are probably already present

Invasive species threaten global biodiversity, food security and ecosystem function. Such incursions present challenges to agriculture where invasive species cause significant crop damage and require major economic investment to control production losses. Pest risk analysis (PRA) is key to prioritize agricultural biosecurity efforts, but is hampered by incomplete knowledge of current crop pest and pathogen distributions. Here, we develop predictive models of current pest distributions and test these models using new observations at subnational resolution. We apply generalized linear models (GLM) to estimate presence probabilities for 1,739 crop pests in the CABI pest distribution database. We test model predictions for 100 unobserved pest occurrences in the People's Republic of China (PRC), against observations of these pests abstracted from the Chinese literature. This resource has hitherto been omitted from databases on global pest distributions. Finally, we predict occurrences of all unobserved pests globally. Presence probability increases with host presence, presence in neighbouring regions, per capita GDP and global prevalence. Presence probability decreases with mean distance from coast and known host number per pest. The models are good predictors of pest presence in provinces of the PRC, with area under the ROC curve (AUC) values of 0.75-0.76. Large numbers of currently unobserved, but probably present pests (defined here as unreported pests with a predicted presence probability >0.75), are predicted in China, India, southern Brazil and some countries of the former USSR. We show that GLMs can predict presences of pseudoabsent pests at subnational resolution. The Chinese literature has been largely inaccessible to Western academia but contains important information that can support PRA. Prior studies have often assumed that unreported pests in a global distribution database represent a true absence. Our analysis provides a method for quantifying pseudoabsences to enable improved PRA and species distribution modelling.

A new mechanistic model of weather-dependent Septoria tritici blotch disease risk

We present a new mechanistic model for predicting Septoria tritici blotch (STB) disease, parameterized with experimentally derived data for temperature- and wetness-dependent germination, growth and death of the causal agent, Zymoseptoria tritici. The output of this model (A) was compared with observed disease data for UK wheat over the period 2002-2016. In addition, we compared the output of a second model (B), in which experimentally derived parameters were replaced by a modified version of a published Z. tritici thermal performance equation, with the same observed disease data. Neither model predicted observed annual disease, but model A was able to differentiate UK regions with differing average disease risks over the entire period. The greatest limitations of both models are: broad spatial resolution of the climate data, and lack of host parameters. Model B is further limited by its lack of explicitly defined pathogen death, leading to a cumulative overestimation of disease over the course of the growing season. Comparison of models A and B demonstrates the importance of accounting for the temperature-dependency of pathogen processes important in the initiation and progression of disease. However, effective modelling of STB will probably require similar experimentally derived parameters for host and environmental factors, completing the disease triangle. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

Multiple-Disease System in Coffee: From Crop Loss Assessment to Sustainable Management

Assessment of crop loss due to multiple diseases and pests (D&P) is a necessary step in designing sustainable crop management systems. Understanding the drivers of D&P development and yield loss helps identify leverage points for crop health management. Crop loss assessment is also necessary for the quantification of D&P regulation service to identify promising systems where ecosystem service provision is optimized. In perennial crops, assessment of crop losses due to D&P is difficult, as injuries can affect yield over years. In coffee, one of the first perennials in which crop loss trials were implemented, crop losses concurrent with injuries were found to be approximately 50% lower than lagged losses that originated following the death of productive branches due to D&P. Crop losses can be assessed by field trials and surveys, where yield reduction factors such as the number of productive branches that have died are quantified, and by modeling, where damage mechanisms for each injury are considered over several years.

Climate Change, Carbon Dioxide, and Pest Biology, Managing the Future: Coffee as a Case Study

The challenge of maintaining sufficient food, feed, fiber, and forests, for a projected end of century population of between 9–10 billion in the context of a climate averaging 2–4 °C warmer, is a global imperative. However, climate change is likely to alter the geographic ranges and impacts for a variety of insect pests, plant pathogens, and weeds, and the consequences for managed systems, particularly agriculture, remain uncertain. That uncertainty is related, in part, to whether pest management practices (e.g., biological, chemical, cultural, etc.) can adapt to climate/CO2 induced changes in pest biology to minimize potential loss. The ongoing and projected changes in CO2, environment, managed plant systems, and pest interactions, necessitates an assessment of current management practices and, if warranted, development of viable alternative strategies to counter damage from invasive alien species and evolving native pest populations. We provide an overview of the interactions regarding pest biology and climate/CO2; assess these interactions currently using coffee as a case study; identify the potential vulnerabilities regarding future pest impacts; and discuss possible adaptive strategies, including early detection and rapid response via EDDMapS (Early Detection & Distribution Mapping System), and integrated pest management (IPM), as adaptive means to improve monitoring pest movements and minimizing biotic losses while improving the efficacy of pest control.

Potential for re-emergence of wheat stem rust in the United Kingdom

Wheat stem rust, a devastating disease of wheat and barley caused by the fungal pathogen Puccinia graminis f. sp. tritici, was largely eradicated in Western Europe during the mid-to-late twentieth century. However, isolated outbreaks have occurred in recent years. Here we investigate whether a lack of resistance in modern European varieties, increased presence of its alternate host barberry and changes in climatic conditions could be facilitating its resurgence. We report the first wheat stem rust occurrence in the United Kingdom in nearly 60 years, with only 20% of UK wheat varieties resistant to this strain. Climate changes over the past 25 years also suggest increasingly conducive conditions for infection. Furthermore, we document the first occurrence in decades of P. graminis on barberry in the UK . Our data illustrate that wheat stem rust does occur in the UK and, when climatic conditions are conducive, could severely harm wheat and barley production.

Tackling emerging fungal threats to animal health, food security and ecosystem resilience

Emerging infections caused by fungi have become a widely recognized global phenomenon. Their notoriety stems from their causing plagues and famines, driving species extinctions, and the difficulty in treating human mycoses alongside the increase of their resistance to antifungal drugs. This special issue comprises a collection of articles resulting from a Royal Society discussion meeting examining why pathogenic fungi are causing more disease now than they did in the past, and how we can tackle this rapidly emerging threat to the health of plants and animals worldwide.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'.

Influence of Environmental Conditions and Genetic Background of Arabica Coffee (C. arabica L) on Leaf Rust (Hemileia vastatrix) Pathogenesis

Global warming is a major threat to agriculture worldwide. Between 2008 and 2013, some coffee producing countries in South and Central America suffered from severe epidemics of coffee leaf rust (CLR), resulting in high economic losses with social implications for coffee growers. The climatic events not only favored the development of the pathogen but also affected the physiological status of the coffee plant. The main objectives of the study were to evaluate how the physiological status of the coffee plant modified by different environmental conditions impact on the pathogenesis of CLR and to identify indicators of the physiological status able to predict rust incidence. Three rust susceptible genotypes (one inbred line and two hybrids) were grown in controlled conditions with a combination of thermal regime (TR), nitrogen and light intensity close to the field situation before being inoculated with the rust fungus Hemileia vastatrix. It has been demonstrated that a TR of 27-22°C resulted in 2000 times higher sporulation than with a TR of 23-18°C. It has been also shown that high light intensity combined with low nitrogen fertilization modified the CLR pathogenesis resulting in huge sporulation. CLR sporulation was significantly lower in the F1 hybrids than in the inbred line. The hybrid vigor may have reduced disease incidence. Among the many parameters studied, parameters related to photosystem II and photosynthetic electron transport chain components appeared as indicators of the physiological status of the coffee plant able to predict rust sporulation intensity. Taken together, these results show that CLR sporulation not only depends on the TR but also on the physiological status of the coffee plant, which itself depends on agronomic conditions. Our work suggests that vigorous varieties combined with a shaded system and appropriate nitrogen fertilization should be part of an agro-ecological approach to disease control.