Climate change impacts on African crop production

According to the most recent IPCC report, changes in climates over the last 30 years have already reduced global agricultural production in the range 1-5 % per decade globally, with particularly negative effects for tropical cereal crops such as maize and rice (Porter et al., 2014). In addition, there is now mounting evidence suggesting that even at low (+2 ºC) levels of warming, agricultural productivity is likely to decline across the globe, but particularly across tropical areas (Challinor et al., 2014). This Working Paper provides an overview of projected climate change impacts on crop production and suitability across Africa, using a combination of literature review, models and new data analysis

Environmental characterisation to guide breeding decisions in a changing climate

Substantial evidence now exists suggesting that agricultural yields will have to increase significantly in order to meet food needs during the 21st century. One such way of increasing yields is to develop high yielding cultivars through crop improvement. This Working Paper summarises the results of a CCAFS project named Target Population of Environments (TPE). The project aimed at providing actionable information to crop breeders and, therefore, inform breeding decisions. We developed and applied a methodology for classifying crop growing environments, determining stress profiles and, finally, assessing the potential benefit of improved breeding practice. We present two contrasting case studies, one for upland rice in central Brazil and another for common beans in Goiás (Brazil). Analyses are also currently being conducted for lowland irrigated rice in Colombia, and plans to conduct research on rice in sub-Saharan Africa. Results of the TPE project are publicly available in the form of dynamic maps and graphs at http://www.ccafs-tpe.org

Métodos alternativos para evaluar expresión diferencial sin réplicas de los tratamientos de materiales rubus glaucus benth tolerantes al ataque de colletotrichum gloesporiodes con el fin de identificar genes de importancia asociados a tolerancia

El cultivo de mora de la zona andina, conocido científicamente como Rubus glaucus se cultiva masivamente en Colombia donde se pueden encontrar diferentes variedades, los cuales pertenecen a la familia Rosacea que incluye otros miembros de gran importancia económica a nivel mundial como la fresa, la pera, la cereza, el durazno, la frambuesa y la rosa, entre otras.Muchas familias de la zona andina dependen del cultivo de mora (Rubus glaucus, BENTH), sin embargo, la productividad de este cultivo no es la ideal debido a las enfermedades que lo afectan, entre las que se encuentra la antracnosis causada por Colletotrichum gloeosporioides como una de las de mayor relevancia (López-Vásquez et al., 2013). En la región cafetera de Colombia se ha identificado que en el 52,9% de los casos esta enfermedad afecta la productividad de los cultivos de mora, catalogándola como una de las más importantes (Botero et al., 2002). Este trabajo se enfoca en identificar los genes en Rubus glaucus, BENTH tolerantes al ataque de Colletotrichum gloeosporioides, a partir de un análisis de expresión diferencial. Se usaron 3 grupos, un material tolerante inoculado con el patógeno, un material susceptible inoculado con el patógeno y un material susceptible sin inocular. El análisis de expresión diferencial viene después de realizar la secuenciación por RNA-seq y el ensamblaje del transcriptoma de Rubus glaucus, BENTH, los cuales fueron desarrollados por el grupo de investigación en Biodiversidad y Biotecnológica de la Universidad Tecnológica de Pereira. Por los altos costos que representan los análisis de secuenciación RNA-seq, sólo se contó con una réplica de este experimento. El presente proyecto parte con un estudio del estado del arte de los experimentos RNA-seq para identificar métodos que permitan hacer análisis de expresión diferencial cuando sólo se cuenta con una réplica, después de ser identificados

Analysis of threats to South American flora and its implications for conservation

South America houses a significant proportion of the world's plant diversity and therefore merits conservation attention. However, ongoing habitat fragmentation, degradation and destruction of natural habitats threaten biodiversity. A set of seven threats to natural ecosystems derived from a previous study (Jarvis et al. 2010), combined with a dataset of occurrences from 16,339 species, and also with the World Database of Protected Areas were used to analyse the patterns of threats to flora in South America and its conservation. Species richness per ?50 km side cell ranged from 1 to 2149 taxa, but with most of the areas presenting between 1 and 58 taxa. Population accessibility, expansion of agriculture and grazing pressure were found to be the key drivers of immediate extinction risk. A considerable (78.4%) number of species presented at least one population under high threat due to the expansion and intensification of these anthropogenic activities. In addition, some 13.8% of the analysed species presented up to 80% of their populations at risk of extinction (high threat index). On the conservation side, 82.3% of the analysed taxa have at least one population occurring within a protected site. However, it is important to note that for a protected area system to be effective and efficient, the conservation of within-taxon genetic diversity is required. The expansion, monitoring and strengthening of 24 existing protected areas holding up to 70% of South American plant diversity is suggested; as is the revision of seven additional sites where up to 200 species not currently conserved are present. Critical areas to monitor, expand and strengthen are mainly located in the Ecuadorian and Colombian Andes, southern Paraguay, the Guyana shield, southern Brazil, and Bolivia

Empirical approaches for assessing impacts of climate change on agriculture: The EcoCrop model and a case study with grain sorghum

Climate has been changing in the last three decades and will continue changing regardless of any mitigation strategy. Agriculture is a climate-dependent activity and hence is highly sensitive to climatic changes and climate variability. Nevertheless, there is a knowledge gap when agricultural researchers intend to assess the production of minor crops for which data or models are not available. Therefore, we integrated the current expert knowledge reported in the FAO-EcoCrop database, with the basic mechanistic model (also named EcoCrop), originally developed by Hijmans et al. (2001). We further developed the model, providing calibration and evaluation procedures. To that aim, we used sorghum (Sorghum bicolor Moench) as a case study and both calibrated EcoCrop for the sorghum crop and analyzed the impacts of the SRES-A1B 2030s climate on sorghum climatic suitability. The model performed well, with a high true positive rate (TPR) and a low false negative rate (FNR) under present conditions when assessed against national and subnational agricultural statistics (min TPR = 0.967, max FNR = 0.026). The model predicted high sorghum climatic suitability in areas where it grows optimally and matched the sorghum geographic distribution fairly well. Negative impacts were predicted by 2030s. Vulnerabilities in countries where sorghum cultivation is already marginal are likely (with a high degree of certainty): the western Sahel region, southern Africa, northern India, and the western coast of India are particularly vulnerable. We highlight the considerable opportunity of using EcoCrop to assess global food security issues, broad climatic constraints and regional crop-suitability shifts in the context of climate change and the possibility of coupling it with other large-area approaches

Downscaling Global Circulation Model Outputs: The Delta Method Decision and Policy Analysis Working Paper No. 1

There has been significant scientific discord over what the best resolution for forecasting the impacts of climate change on agriculture and biodiversity is. Several researchers (particularly climatic researchers) state that original GCM (General Circulation Model) resolution should be kept in order to manage, understand and not bias or alter uncertainties produced by GCMs themselves; however, a coarse resolution of 100 or 200km (or even more) is simply not practical for assessing agricultural landscapes, particularly in the tropics, where orographic and climatic conditions vary significantly across relatively small distances. Moreover, changes in topography and climate variables are not the only factors accounting for variability in agriculture; soils and socioeconomic drivers, also often differ over small distances, influencing agro-ecosystems, increasing uncertainties, and making forecasting and assessment models more inaccurate and complicated to calibrate. Here we present a downscaling method as well as a global database on climate change data that can be used for crop modeling, niche modeling, and more generally, for assessing impacts of climate change on agriculture at fine scales, using any approach that might require monthly maximum, minimum, mean temperatures and monthly total precipitation (from which a set of bioclimatic indices were also derived). This database (with a total of 441 different scenarios –the sum of 24, 20 and 19 GCMs, times 7 time-slices) complements other existing databases that also use downscaling but are only available either for a limited set of GCMs, time-slices, regions, or for variables or at coarser resolution. As such, we provide the most current and comprehensive set of climate change ready-to-use datasets, available online at https://ccafs-climate.org

GBIF: mobilising information for adapting agriculture to climate change

Poster presented at Climate Change, Global Risk, Challenges & Decisions, Copenhagen (Denmark), 10-12 March 200