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"Wheeler, Tim"
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Climate change impacts on global food security
Climate change could potentially interrupt progress toward a world without hunger. A robust and coherent global pattern is discernible of the impacts of climate change on crop productivity that could have consequences for food availability. The stability of whole food systems may be at risk under climate change because of short-term variability in supply. However, the potential impact is less clear at regional scales, but it is likely that climate variability and change will exacerbate food insecurity in areas currently vulnerable to hunger and undernutrition. Likewise, it can be anticipated that food access and utilization will be affected indirectly via collateral effects on household and individual incomes, and food utilization could be impaired by loss of access to drinking water and damage to health. The evidence supports the need for considerable investment in adaptation and mitigation actions toward a \"climate-smart food system\" that is more resilient to climate change influences on food security.
Journal Article
Learning Discrete Bayesian Networks from Continuous Data
Learning Bayesian networks from raw data can help provide insights into the relationships between variables. While real data often contains a mixture of discrete and continuous-valued variables, many Bayesian network structure learning algorithms assume all random variables are discrete. Thus, continuous variables are often discretized when learning a Bayesian network. However, the choice of discretization policy has significant impact on the accuracy, speed, and interpretability of the resulting models. This paper introduces a principled Bayesian discretization method for continuous variables in Bayesian networks with quadratic complexity instead of the cubic complexity of other standard techniques. Empirical demonstrations show that the proposed method is superior to the established minimum description length algorithm. In addition, this paper shows how to incorporate existing methods into the structure learning process to discretize all continuous variables and simultaneously learn Bayesian network structures.
Journal Article
Climate change impacts on crop productivity in Africa and South Asia
Climate change is a serious threat to crop productivity in regions that are already food insecure. We assessed the projected impacts of climate change on the yield of eight major crops in Africa and South Asia using a systematic review and meta-analysis of data in 52 original publications from an initial screen of 1144 studies. Here we show that the projected mean change in yield of all crops is − 8% by the 2050s in both regions. Across Africa, mean yield changes of − 17% (wheat), − 5% (maize), − 15% (sorghum) and − 10% (millet) and across South Asia of − 16% (maize) and − 11% (sorghum) were estimated. No mean change in yield was detected for rice. The limited number of studies identified for cassava, sugarcane and yams precluded any opportunity to conduct a meta-analysis for these crops. Variation about the projected mean yield change for all crops was smaller in studies that used an ensemble of > 3 climate (GCM) models. Conversely, complex simulation studies that used biophysical crop models showed the greatest variation in mean yield changes. Evidence of crop yield impact in Africa and South Asia is robust for wheat, maize, sorghum and millet, and either inconclusive, absent or contradictory for rice, cassava and sugarcane.
Journal Article
Impact of progressive global warming on the global-scale yield of maize and soybean
Global surface temperature is projected to warm over the coming decades, with regional differences expected in temperature change, rainfall and the frequency of extreme events. Temperature is a major determinant of crop growth and development, affecting planting date, growing season length and yield. We investigated the effects of increments of mean global temperature warming from 0.5 °C to 4 °C on soybean and maize development and yield, both globally and for the main producing countries, and simulated adaptation through changing planting date and variety. Increasing temperature resulted in reduced growing season lengths and ultimately reduced yields for both crops. The global yield for maize decreased as temperature increased, although the severity of the decrease was dependent on geographic region. Small temperature increases of 0.5 °C had no effect on soybean yield, although yield decreased as temperature increased. These negative effects, however, were partly compensated for by the implementation of adaptation strategies including planting earlier in the season and changing variety. The degree of compensation was dependent on geographical area and crop, with maize adaptation delaying the negative effects of temperature on yield, compared to soybean adaptation which increased yield in China, India and Korea DPR as well as delaying the effects in the remaining countries. The results of this paper indicate the degree to which farmer-controlled adaptation strategies can alleviate the negative impacts of increasing temperature on two major crop species.
Journal Article
Convergent evolution of a symbiotic duet: The case of the lichen genus Polychidium (Peltigerales, Ascomycota)
Premise of the study: Thallus architecture has long been a powerful guide for classifying lichens and has often trumped photobiont association and ascomatal type, but the reliability of these characters to predict phylogenetic affinity has seldom been tested. The cyanolichen genus Polychidium unites species that have strikingly similar gross morphology but consort with different photobiont genera. If Polychidium were found to be monophyletic, photobiont switching among closely related species would be suggested. If, however, species were found to arise in different lineages, a convergent body plan and ascomatal type evolution would be inferred. Methods: We tested the monophyly of Polychidium with a multilocus phylogeny based on nuclear and mitochondrial sequence data from all known Peltigeralean families and reconstructed ancestral states for specific thallus architecture and ascomatal ontogeny types relative to Polychidium and other clades. Key results: We found that Polychidium consists of two species groups that arose independently in different suborders within the Peltigerales, associated with Nostoc and Scytonema photobionts, respectively. We infer from ancestral character state reconstruction that dendroid thallus architecture evolved independently in these two lineages. Conclusions: The independent development of similar dendroid thallus architecture in different fungal suborders with different photobionts represents a clear and previously overlooked example of convergent evolution in lichens. Our results also suggest a pattern of character state conservation, loss, and reversion in ascomatal ontogeny types, hitherto considered conserved traits useful for higher level ascomycete systematics.
Journal Article
Rural household vulnerability to climate risk in Uganda
Vulnerability assessment is fundamental for informing adaptation to climate change policy. The aim of this study is to evaluate the vulnerability of rural subsistence farmers in Uganda to climate risk. A mixed methods approach used semi-structured and guided interviews, and participatory techniques to explore perception, livelihood response and socio-economic status. Perception of climate risk varied, with wealthier farmers perceiving drought as highest risk, whilst poorer farmers perceived extreme heavy rainfall. Farmers implemented many general livelihood coping and anticipatory responses (54.7 %) to perceived impacts from drought, rainfall variability and extreme heavy rainfall. Examples included food storage, livestock maintenance and planting drought-resistant varieties. Other responses (45.3 %) were specific to individual climatic events, and farmers had no response to cope with rainfall variability. Climate risk was not the only driver of vulnerability. Soil infertility, pests and diseases, and economic instability also sustained decreasing trends in income. Adaptive capacity of households differed with external and internal attributes of sensitivity. Farmers with more land, education, access to governmental extension, a non-farm livelihood, larger households and older age had more capacity to buffer shock through increased assets and entitlements than poorer farmers who were more likely to engage in opportunistic behaviour like casual labouring. Few livelihood responses associated with perceived threat from the climate indicating response to a broader range of stressors. Conclusions determined inequality in livelihood response as a fundamental driver in households’ ability to cope and adapt to climate risk.
Journal Article
METHODS AND RESOURCES FOR CLIMATE IMPACTS RESEARCH
[...] using existing projects and studies, we ask how, given the competing demands on computer power, climate impacts research can best use the methods and computational resources at its disposal. [...] multimodel ensembles are an efficient way of providing information for climate impacts because a range of existing models are used, thus making good use of globally available computer resources (see, e.g., Palmer et al. 2004, 2005). Because the models used for both seasonal and multidecadal time scales are based on simulation of the same fundamental processes, skill at the shorter time scale in part supports our confidence in longer-term projections.
Journal Article