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- Nurihun, Biruk Ayalew, 1983-, et al.
(författare)
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Impact of climate and management on coffee berry disease and yield in coffee's native range
- 2024
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Ingår i: Basic and Applied Ecology. - 1439-1791 .- 1618-0089. ; 76, s. 25-34
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Tidskriftsartikel (refereegranskat)abstract
- Climate change might increase plant diseases, reduce crop yields and threaten the livelihoods of millions of smallholder farmers globally. It is thus important to understand the relationships between climate, disease levels and yield to improve management strategies for sustainable agroforestry in a changing climate. One of the major threats to coffee production in Africa is the coffee berry disease (Colletotrichum kahawae). To investigate the effects of climatic and management variables on coffee berry disease (CBD) incidence and yield, we recorded minimum and maximum temperature and relative humidity, as well as CBD and yield, along a broad environmental and management gradient in southwestern Ethiopia during two consecutive years. CBD was affected by several climatic and management variables. For example, CBD incidence increased with minimum temperature during the fruit expansion stage, and decreased with minimum temperature during the endosperm filling stage. CBD incidence was negatively affected by the proportion of resistant cultivars, whereas the coffee structure index (pruning) had no effect on disease incidence. Coffee yield decreased with increasing minimum temperature during the flowering period in 2018 and maximum temperature during the fruit developmental period in 2019. Coffee yield was negatively affected by canopy cover and positively affected by the coffee structure index in both years. Our findings highlight that CBD and yield were affected by different climatic and management variables. Yet, managing for low disease levels and high yield is practically difficult due to season -dependent effects of several climatic variables. One way to break the correlation of climatic variables between seasons might be to take advantage of differences among shade trees in the presence or timing of leaf drop. To reduce CBD incidence, using resistant cultivars is an effective strategy, but this might threaten the wild coffee genetic reservoir.
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- Nurihun, Biruk Ayalew, 1983-, et al.
(författare)
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Using local knowledge to reconstruct climate-mediated changes in disease dynamics and yield-A case study on Arabica coffee in its native range
- 2024
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Ingår i: Plants, People, Planet. - 2572-2611.
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Tidskriftsartikel (refereegranskat)abstract
- Societal Impact StatementAdapting agriculture to climate change requires an understanding of the long-term relationship between climate, disease dynamics, and yield. While some countries have monitored major crop diseases for decades or centuries, comparable data is scarce or non-existent for many countries that are most vulnerable to climate change. For this, a novel approach was developed to reconstruct climate-mediated changes in disease dynamics and yield. Here, a case study on Arabica coffee in its area of origin demonstrates how to combine local knowledge, climate data, and spatial field surveys to reconstruct disease and yield time series and to postulate and test hypotheses for climate-disease-yield relationships.Summary While some countries have monitored crop diseases for several decades or centuries, other countries have very limited historical time series. In such areas, we lack data on long-term patterns and drivers of disease dynamics, which is important for developing climate-resilient disease management strategies.We adopted a novel approach, combining local knowledge, climate data, and spatial field surveys to understand long-term climate-mediated changes in disease dynamics in coffee agroforestry systems. For this, we worked with 58 smallholder farmers in southwestern Ethiopia, the area of origin of Arabica coffee.The majority of farmers perceived an increase in coffee leaf rust and a decrease in coffee berry disease, whereas perceptions of changes in coffee wilt disease and Armillaria root rot were highly variable among farmers. Climate data supported farmers' understanding of the climatic drivers (increased temperature, less rainy days) of these changes. Temporal disease-climate relationships were matched by spatial disease-climate relationships, as expected with space-for-time substitution.Understanding long-term disease dynamics and yield is crucial to adapt disease management to climate change. Our study demonstrates how to combine local knowledge, climate data and spatial field surveys to reconstruct disease time series and postulate hypotheses for disease-climate relationships in areas where few long-term time series exist.
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- Zignol, Francesco, et al.
(författare)
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The understory microclimate in agroforestry now and in the future-a case study of Arabica coffee in its native range
- 2023
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Ingår i: Agricultural and Forest Meteorology. - 0168-1923 .- 1873-2240. ; 340
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Tidskriftsartikel (refereegranskat)abstract
- Climate change is having a major impact on crop production and food security worldwide, and particularly so for smallholder farmers. As agroforestry is common with smallholder farmers, it is important to not only model the macroclimate, but also the microclimate that crops experience below the canopies. However, there are few highresolution spatiotemporal climate projections for forest understories, because of constraints related to the lack of i) development of models for downscaling global climate projections, ii) high-resolution gridded datasets of environmental factors influencing microclimate, and iii) spatially replicated in-situ microclimate measurements. We focused on a landscape in southwestern Ethiopia where Arabica coffee originated, and, in the present day, is commonly grown as a shade crop. We first examined the relative contribution of in-situ field measurements vs. GIS-derived estimates of vegetation and topographic features in explaining in-situ microclimate. Second, we used a statistical downscaling approach to obtain past and future microclimate maps at 30-meter spatial resolution for the part of the landscape that is covered by trees. Predictive models using in-situ variables performed equal to models with GIS variables, indicating that remote sensing data might substitute for in-situ field measurements. Vegetation and topographic features were both important in explaining microclimatic variation. Our spatiotemporal projections of the microclimate indicate that coffee farming might have to relocate to higher altitudes due to increasing temperatures, that vegetation might buffer the macroclimate at middle altitudes to some extent, and that decreasing trends in relative humidity at the beginning of the wet season might become problematic for coffee production. Taken together, our findings demonstrate that we can rely on remote sensing data to create microclimate maps in landscapes where in-situ field measurements are challenging, and we suggest how these microclimate projections can be used as a tool to promote climate-resilient agriculture at the local and landscape levels.
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