Leaf functional traits and pathogens: Linking coffee leaf rust with intraspecific trait variation in diversified agroecosystems.

Research has demonstrated that intraspecific functional trait variation underpins plant responses to environmental variability. However, few studies have evaluated how trait variation shifts in response to plant pathogens, even though pathogens are a major driver of plant demography and diversity, and despite evidence of plants expressing distinct strategies in response to pathogen pressures. Understanding trait-pathogen relationships can provide a more realistic understanding of global patterns of functional trait variation. We examined leaf intraspecific trait variability (ITV) in response to foliar disease severity, using Coffea arabica cv. Caturra as a model species. We quantified coffee leaf rust (CLR) severity-a fungal disease prominent in coffee systems-and measured key coffee leaf functional traits under contrasting, but widespread, management conditions in an agroforestry system. We found that coffee plants express significant ITV, which is largely related to shade tree treatment and leaf position within coffee canopy strata. Yet within a single plant canopy stratum, CLR severity increased with increasing resource conserving trait values. However, coffee leaves with visible signs of disease expressed overall greater resource acquiring trait values, as compared to plants without visible signs of disease. We provide among the first evidence that leaf traits are correlated with foliar disease severity in coffee, and that functional trait relationships and syndromes shift in response to increased disease prevalence in this plant-pathogen system. In doing so, we address a vital gap in our understanding of global patterns of functional trait variation and highlight the need to further explore the potential role of pathogens within established global trait relationships and spectra.

Tree Effects on Coffee Leaf Rust at Field and Landscape Scales.

Although integrating trees into agricultural systems (i.e., agroforestry systems) provides many valuable ecosystem services, the trees can also interact with plant diseases. We demonstrate that a detailed understanding of how plant diseases interact with trees in agroforestry systems is necessary to identify key tree canopy characteristics, leaf traits, spatial arrangements, and management options that can help control plant diseases at different spatial scales. We focus our analysis on how trees affect coffee leaf rust, a major disease affecting one of the world's most significant crop commodities. We show that trees can both promote and discourage the development of coffee leaf rust at the plot scale via microclimate modifications in the understory. Based on our understanding of the role of tree characteristics in shaping the microclimate, we identify several canopy characteristics and leaf traits that can help manage coffee leaf rust at the plot scale: namely, thin canopies with high openness, short base height, horizontal branching, and small, dentate leaves. In contrast, at the edge of coffee farms, having large trees with high canopy volume and small, thick, waxy leaves is more useful to reduce throughflow wind speeds and intercept the airborne dispersal of urediniospores, an important consideration to control disease at the landscape scale. Seasonal pruning can help shape trees into the desired form, and trees can be spatially arranged to optimize desired effects. This case study demonstrates the added value of combining process-based epidemiology studies with functional trait ecology to improve disease management in agroforestry systems.

Transformation of coffee-growing landscapes across Latin America. A review.

In Latin America, the cultivation of Arabica coffee (Coffea arabica) plays a critical role in rural livelihoods, biodiversity conservation, and sustainable development. Over the last 20 years, coffee farms and landscapes across the region have undergone rapid and profound biophysical changes in response to low coffee prices, changing climatic conditions, severe plant pathogen outbreaks, and other drivers. Although these biophysical transformations are pervasive and affect millions of rural livelihoods, there is limited information on the types, location, and extent of landscape changes and their socioeconomic and ecological consequences. Here we review the state of knowledge on the ongoing biophysical changes in coffee-growing regions, explore the potential socioeconomic and ecological impacts of these changes, and highlight key research gaps. We identify seven major land-use trends which are affecting the sustainability of coffee-growing regions across Latin America in different ways. These trends include (1) the widespread shift to disease-resistant cultivars, (2) the conventional intensification of coffee management with greater planting densities, greater use of agrochemicals and less shade, (3) the conversion of coffee to other agricultural land uses, (4) the introduction of Robusta coffee (Coffea canephora) into areas not previously cultivated with coffee, (5) the expansion of coffee into forested areas, (6) the urbanization of coffee landscapes, and (7) the increase in the area of coffee produced under voluntary sustainability standards. Our review highlights the incomplete and scattered information on the drivers, patterns, and outcomes of biophysical changes in coffee landscapes, and lays out a detailed research agenda to address these research gaps and elucidate the effects of different landscape trajectories on rural livelihoods, biodiversity conservation, and other aspects of sustainable development. A better understanding of the drivers, patterns, and consequences of changes in coffee landscapes is vital for informing the design of policies, programs, and incentives for sustainable coffee production. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13593-021-00712-0.

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.

Concurrent starch accumulation in stump and high fruit production in coffee (Coffea arabica).

In coffee, fruit production on a given shoot drops after some years of high yield, triggering pruning to induce resprouting. The timing of pruning is a crucial farmer's decision affecting yield and labour. One reason for fruit production drop could be the exhaustion of resources, particularly the non-structural carbohydrates (NSC). To test this hypothesis in a Coffea L. arabica agroforestry system, we measured the concentrations of NSC, carbon (C) and nitrogen (N) in leaves, stems and stumps of the coffee plants, 2 and 5 years after pruning. We also compared shaded vs full sun plants. For that purpose, both analytical reference and visible and near infrared reflectance spectroscopy (VNIRS) methods were used. As expected, concentrations of biochemical variables linked to photosynthesis activity (N, glucose, fructose, sucrose) decreased from leaves to stems, and then to stumps. In contrast, variables linked more closely to plant structure and reserves (total C, C:N ratio, starch concentration) were higher in long lifespan organs like stumps. Shading had little effect on most measured parameters, contrary to expectations. Concentrations of N, glucose and fructose were higher in 2-year-old organs. Conversely, starch concentration in perennial stumps was three times higher 5 years after pruning than 2 years after pruning, despite high fruit production. Therefore, the drop in fruit production occurring after 5-6 years was not due to a lack of NSC on plant scale. Starch accumulation in perennial organs concurrently to other sinks, such as fruit growth, could be considered as a 'survival' strategy, which may be a relic of the behaviour of wild coffee (a tropical shade-tolerant plant). This study confirmed that VNIRS is a promisingly rapid and cost-effective option for starch monitoring (coefficient of determination for validation, R2val = 0.91), whereas predictions were less accurate for soluble sugars, probably due to their too similar spectral signature.

Unraveling the Complexity of Coffee Leaf Rust Behavior and Development in Different Coffea arabica Agroecosystems.

Crop health management systems can be designed according to practices that help to reduce crop losses by restricting pathogen development and promoting host plant growth. A good understanding of pathogen and host dynamics, which are interdependent, is therefore needed. In this article, we used a holistic approach to explain the behavior of coffee leaf rust (CLR), a major coffee disease. We monitored coffee plant and CLR dynamics simultaneously in plots under different disease management and agroforestry systems. Diseased leaves were also collected to characterize inoculum stock and rust life stages (latent rust area, area with uredospores, necrosis due to rust) through picture analysis. We used structural equation modeling to obtain an overview of CLR pathosystem functioning on a plant scale. This overview integrates processes such as disease dilution by host leaf renewal, direct and indirect effects of fruit load on CLR development, antagonistic effects of shading depending on rust life stages, the tonic effect of copper-based fungicides on leaf retention, and effects on rust life stages depending on fungicide types. From our results, we also deduced that the inoculum stock could be calculated in unsprayed plots from the rust area with uredospores, with uredospores at 58 × 103 cm-2, on average.

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition.

The idea that noncrop habitat enhances pest control and represents a win-win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win-win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

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.

Effects of microclimatic variables on the symptoms and signs onset of Moniliophthora roreri, causal agent of Moniliophthora pod rot in cacao.

Moniliophthora Pod Rot (MPR) caused by the fungus Moniliophthora roreri (Cif.) Evans et al., is one of the main limiting factors of cocoa production in Latin America. Currently insufficient information on the biology and epidemiology of the pathogen limits the development of efficient management options to control MPR. This research aims to elucidate MPR development through the following daily microclimatic variables: minimum and maximum temperatures, wetness frequency, average temperature and relative humidity in the highly susceptible cacao clone Pound-7 (incidence = 86% 2008-2013 average). A total of 55 cohorts totaling 2,268 pods of 3-10 cm length, one to two months of age, were tagged weekly. Pods were assessed throughout their lifetime, every one or two weeks, and classified in 3 different categories: healthy, diseased with no sporulation, diseased with sporulating lesions. As a first step, we used Generalized Linear Mixed Models (GLMM) to determine with no a priori the period (when and for how long) each climatic variable was better related with the appearance of symptoms and sporulation. Then the significance of the candidate variables was tested in a complete GLMM. Daily average wetness frequency from day 14 to day 1, before tagging, and daily average maximum temperature from day 4 to day 21, after tagging, were the most explanatory variables of the symptoms appearance. The former was positively linked with the symptoms appearance when the latter exhibited a maximum at 30°C. The most important variables influencing sporulation were daily average minimum temperature from day 35 to day 58 and daily average maximum temperature from day 37 to day 48, both after tagging. Minimum temperature was negatively linked with the sporulation while maximum temperature was positively linked. Results indicated that the fungal microclimatic requirements vary from the early to the late cycle stages, possibly due to the pathogen's long latent period. This information is valuable for development of new conceptual models for MPR and improvement of control methods.

Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee.

The assessment of crop yield losses is needed for the improvement of production systems that contribute to the incomes of rural families and food security worldwide. However, efforts to quantify yield losses and identify their causes are still limited, especially for perennial crops. Our objectives were to quantify primary yield losses (incurred in the current year of production) and secondary yield losses (resulting from negative impacts of the previous year) of coffee due to pests and diseases, and to identify the most important predictors of coffee yields and yield losses. We established an experimental coffee parcel with full-sun exposure that consisted of six treatments, which were defined as different sequences of pesticide applications. The trial lasted three years (2013-2015) and yield components, dead productive branches, and foliar pests and diseases were assessed as predictors of yield. First, we calculated yield losses by comparing actual yields of specific treatments with the estimated attainable yield obtained in plots which always had chemical protection. Second, we used structural equation modeling to identify the most important predictors. Results showed that pests and diseases led to high primary yield losses (26%) and even higher secondary yield losses (38%). We identified the fruiting nodes and the dead productive branches as the most important and useful predictors of yields and yield losses. These predictors could be added in existing mechanistic models of coffee, or can be used to develop new linear mixed models to estimate yield losses. Estimated yield losses can then be related to production factors to identify corrective actions that farmers can implement to reduce losses. The experimental and modeling approaches of this study could also be applied in other perennial crops to assess yield losses.

Towards a Collaborative Research: A Case Study on Linking Science to Farmers' Perceptions and Knowledge on Arabica Coffee Pests and Diseases and Its Management.

The scientific community has recognized the importance of integrating farmer's perceptions and knowledge (FPK) for the development of sustainable pest and disease management strategies. However, the knowledge gap between indigenous and scientific knowledge still contributes to misidentification of plant health constraints and poor adoption of management solutions. This is particularly the case in the context of smallholder farming in developing countries. In this paper, we present a case study on coffee production in Uganda, a sector depending mostly on smallholder farming facing a simultaneous and increasing number of socio-ecological pressures. The objectives of this study were (i) to examine and relate FPK on Arabica Coffee Pests and Diseases (CPaD) to altitude and the vegetation structure of the production systems; (ii) to contrast results with perceptions from experts and (iii) to compare results with field observations, in order to identify constraints for improving the information flow between scientists and farmers. Data were acquired by means of interviews and workshops. One hundred and fifty farmer households managing coffee either at sun exposure, under shade trees or inter-cropped with bananas and spread across an altitudinal gradient were selected. Field sampling of the two most important CPaD was conducted on a subset of 34 plots. The study revealed the following findings: (i) Perceptions on CPaD with respect to their distribution across altitudes and perceived impact are partially concordant among farmers, experts and field observations (ii) There are discrepancies among farmers and experts regarding management practices and the development of CPaD issues of the previous years. (iii) Field observations comparing CPaD in different altitudes and production systems indicate ambiguity of the role of shade trees. According to the locality-specific variability in CPaD pressure as well as in FPK, the importance of developing spatially variable and relevant CPaD control practices is proposed.

Shade Effects on the Dispersal of Airborne Hemileia vastatrix Uredospores.

Hemileia vastatrix caused a severe epidemic in Central America in 2012-13. The gradual development of that epidemic on nearly a continental scale suggests that dispersal at different scales played a significant role. Shade has been proposed as a way of reducing uredospore dispersal. The effect of shade (two strata: Erythrina poeppigiana below and Chloroleucon eurycyclum above) and full sun on H. vastatrix dispersal was studied with Burkard traps in relation to meteorological records. Annual and daily patterns of dispersal were observed, with peaks of uredospore capture obtained during wet seasons and in the early afternoon. A maximum of 464 uredospores in 1 day (in 14.4 m(3) of air) was recorded in October 2014. Interactions between shade/full sun and meteorological conditions were found. Rainfall, possibly intercepted by tree cover and redistributed by raindrops of higher kinetic energy, was the main driver of uredospore dispersal under shade. Wind gusts reversed this effect, probably by inhibiting water accumulation on leaves. Wind gusts also promoted dispersal under dry conditions in full sun, whereas they had no effect under shaded conditions, probably because the canopy blocked the wind. Our results indicate the importance of managing shade cover differentially in rainy versus dry periods to control the dispersal of airborne H. vastatrix uredospores.

Shade tree spatial structure and pod production explain frosty pod rot intensity in cacao agroforests, Costa Rica.

Vegetation composition and plant spatial structure affect disease intensity through resource and microclimatic variation effects. The aim of this study was to evaluate the independent effect and relative importance of host composition and plant spatial structure variables in explaining disease intensity at the plot scale. For that purpose, frosty pod rot intensity, a disease caused by Moniliophthora roreri on cacao pods, was monitored in 36 cacao agroforests in Costa Rica in order to assess the vegetation composition and spatial structure variables conducive to the disease. Hierarchical partitioning was used to identify the most causal factors. Firstly, pod production, cacao tree density and shade tree spatial structure had significant independent effects on disease intensity. In our case study, the amount of susceptible tissue was the most relevant host composition variable for explaining disease intensity by resource dilution. Indeed, cacao tree density probably affected disease intensity more by the creation of self-shading rather than by host dilution. Lastly, only regularly distributed forest trees, and not aggregated or randomly distributed forest trees, reduced disease intensity in comparison to plots with a low forest tree density. A regular spatial structure is probably crucial to the creation of moderate and uniform shade as recommended for frosty pod rot management. As pod production is an important service expected from these agroforests, shade tree spatial structure may be a lever for integrated management of frosty pod rot in cacao agroforests.

Landscape context and scale differentially impact coffee leaf rust, coffee berry borer, and coffee root-knot nematodes.

Crop pest and disease incidences at plot scale vary as a result of landscape effects. Two main effects can be distinguished. First, landscape context provides habitats of variable quality for pests, pathogens, and beneficial and vector organisms. Second, the movements of these organisms are dependent on the connectivity status of the landscape. Most of the studies focus on indirect effects of landscape context on pest abundance through their predators and parasitoids, and only a few on direct effects on pests and pathogens. Here we studied three coffee pests and pathogens, with limited or no pressure from host-specific natural enemies, and with widely varying life histories, to test their relationships with landscape context: a fungus, Hemileia vastatrix, causal agent of coffee leaf rust; an insect, the coffee berry borer, Hypothenemus hampei (Coleoptera: Curculionidae); and root-knot nematodes, Meloidogyne spp. Their incidence was assessed in 29 coffee plots from Turrialba, Costa Rica. In addition, we characterized the landscape context around these coffee plots in 12 nested circular sectors ranging from 50 to 1500 m in radius. We then performed correlation analysis between proportions of different land uses at different scales and coffee pest and disease incidences. We obtained significant positive correlations, peaking at the 150 m radius, between coffee berry borer abundance and proportion of coffee in the landscape. We also found significant positive correlations between coffee leaf rust incidence and proportion of pasture, peaking at the 200 m radius. Even after accounting for plot level predictors of coffee leaf rust and coffee berry borer through covariance analysis, the significance of landscape structure was maintained. We hypothesized that connected coffee plots favored coffee berry borer movements and improved its survival. We also hypothesized that wind turbulence, produced by low-wind-resistance land uses such as pasture, favored removal of coffee leaf rust spore clusters from host surfaces, resulting in increased epidemics. In contrast, root-knot nematode population density was not correlated to landscape context, possibly because nematodes are almost immobile in the soil. We propose fragmenting coffee plots with forest corridors to control coffee berry borer movements between coffee plots without favoring coffee leaf rust dispersal.

Topography and crop management are key factors for the development of american leaf spot epidemics on coffee in costa rica.

ABSTRACT We monitored the development of American leaf spot of coffee, a disease caused by the gemmiferous fungus Mycena citricolor, in 57 plots in Costa Rica for 1 or 2 years in order to gain a clearer understanding of conditions conducive to the disease and improve its control. During the investigation, characteristics of the coffee trees, crop management, and the environment were recorded. For the analyses, we used partial least-squares regression via the spline functions (PLSS), which is a nonlinear extension to partial least-squares regression (PLS). The fungus developed well in areas located between approximately 1,100 and 1,550 m above sea level. Slopes were conducive to its development, but eastern-facing slopes were less affected than the others, probably because they were more exposed to sunlight, especially in the rainy season. The distance between planting rows, the shade percentage, coffee tree height, the type of shade, and the pruning system explained disease intensity due to their effects on coffee tree shading and, possibly, on the humidity conditions in the plot. Forest trees and fruit trees intercropped with coffee provided particularly propitious conditions. Apparently, fertilization was unfavorable for the disease, probably due to dilution phenomena associated with faster coffee tree growth. Finally, series of wet spells interspersed with dry spells, which were frequent in the middle of the rainy season, were critical for the disease, probably because they affected the production and release of gemmae and their viability. These results could be used to draw up a map of epidemic risks taking topographical factors into account. To reduce those risks and improve chemical control, our results suggested that farmers should space planting rows further apart, maintain light shading in the plantation, and prune their coffee trees.