Maize yield and rainfall on different spatial and temporal scales in Southern Brazil

This study aimed to establish relationships between maize yield and rainfall on different temporal and spatial scales, in order to provide a basis for crop monitoring and modelling. A 16-year series of maize yield and daily rainfall from 11 municipalities and micro-regions of Rio Grande do Sul State was used. Correlation and regression analyses were used to determine associations between crop yield and rainfall for the entire crop cycle, from tasseling to 30 days after, and from 5 days before tasseling to 40 days after. Close relationships between maize yield and rainfall were found, particularly during the reproductive period (45-day period comprising the flowering and grain filling). Relationships were closer on a regional scale than at smaller scales. Implications of the crop-rainfall relationships for crop modelling are discussed.

Mining, grievance and conflict in rural Tanzania

This paper provides an extended analysis of the tensions that have surfaced between large-scale mine operators and artisanal miners in gold-rich areas of rural Tanzania. The literature on grievance is used to contextualise, these disputes, the underlying cause of which is artisanal miners' mounting frustration over not being able to secure viable concessions to work. Newly implemented legislation has, for the most part, empowered foreign large-scale mine operators, while simultaneously disempowering indigenous small-scale miners. In many cases, the former have addressed mounting security and community problems on their own. Until the country's major mine operators extend assistance to marginalised small-scale mining groups, the likelihood of violent conflict unfolding between these parties will increase.

Adaptation of crops to climate change through genotypic responses to mean and extreme temperatures

The importance of temperature in the determination of the yield of an annual crop (groundnut; Arachis hypogaea L. in India) was assessed. Simulations from a regional climate model (PRECIS) were used with a crop model (GLAM) to examine crop growth under simulated current (1961-1990) and future (2071-2100) climates. Two processes were examined: the response of crop duration to mean temperature and the response of seed-set to extremes of temperature. The relative importance of, and interaction between, these two processes was examined for a number of genotypic characteristics, which were represented by using different values of crop model parameters derived from experiments. The impact of mean and extreme temperatures varied geographically, and depended upon the simulated genotypic properties. High temperature stress was not a major determinant of simulated yields in the current climate, but affected the mean and variability of yield under climate change in two regions which had contrasting statistics of daily maximum temperature. Changes in mean temperature had a similar impact on mean yield to that of high temperature stress in some locations and its effects were more widespread. Where the optimal temperature for development was exceeded, the resulting increase in duration in some simulations fully mitigated the negative impacts of extreme temperatures when sufficient water was available for the extended growing period. For some simulations the reduction in mean yield between the current and future climates was as large as 70%, indicating the importance of genotypic adaptation to changes in both means and extremes of temperature under climate change. (c) 2006 Elsevier B.V. All rights reserved.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.

Simulation of crop yields using ERA-40: Limits to skill and nonstationarity in weather-yield relationships

Reanalysis data provide an excellent test bed for impacts prediction systems. because they represent an upper limit on the skill of climate models. Indian groundnut (Arachis hypogaea L.) yields have been simulated using the General Large-Area Model (GLAM) for annual crops and the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40). The ability of ERA-40 to represent the Indian summer monsoon has been examined. The ability of GLAM. when driven with daily ERA-40 data, to model both observed yields and observed relationships between subseasonal weather and yield has been assessed. Mean yields "were simulated well across much of India. Correlations between observed and modeled yields, where these are significant. are comparable to correlations between observed yields and ERA-40 rainfall. Uncertainties due to the input planting window, crop duration, and weather data have been examined. A reduction in the root-mean-square error of simulated yields was achieved by applying bias correction techniques to the precipitation. The stability of the relationship between weather and yield over time has been examined. Weather-yield correlations vary on decadal time scales. and this has direct implications for the accuracy of yield simulations. Analysis of the skewness of both detrended yields and precipitation suggest that nonclimatic factors are partly responsible for this nonstationarity. Evidence from other studies, including data on cereal and pulse yields, indicates that this result is not particular to groundnut yield. The detection and modeling of nonstationary weather-yield relationships emerges from this study as an important part of the process of understanding and predicting the impacts of climate variability and change on crop yields.

Strained relations: a critical analysis of the mining conflict in Prestea, Ghana

This paper examines the dynamics of the ongoing conflict in Prestea, Ghana, where indigenous galamsey mining groups are operating illegally on a concession awarded to Bogoso Gold Limited (BGL), property of the Canadian-listed multinational Gold Star Resources. Despite being issued firm orders by the authorities to abandon their activities, galamsey leaders maintain that they are working areas of the concession that are of little interest to the company; they further counter that there are few alternative sources of local employment, which is why they are mining in the first place. Whilst the Ghanaian Government is in the process of setting aside plots to relocate illegal mining parties and is developing alternative livelihood projects, efforts are far from encouraging: in addition to a series of overlooked logistical problems, the areas earmarked for relocation have not yet been prospected to ascertain gold content, and the alternative income-earning activities identified are inappropriate. As has been the case throughout mineral-rich sub-Saharan Africa, the conflict in Prestea has come about largely because the national mining sector reform program, which prioritizes the expansion of predominantly foreign-controlled large-scale projects, has neglected the concerns of indigenous subsistence groups.

Reproductive conflict delays the recovery of an endangered social species

Evolutionary theory predicts that individuals, in order to increase their relative fitness, can evolve behaviours that are detrimental for the group or population. This mismatch is particularly visible in social organisms. Despite its potential to affect the population dynamics of social animals, this principle has not yet been applied to real-life conservation. Social group structure has been argued to stabilize population dynamics due to the buffering effects of nonreproducing subordinates. However, competition for breeding positions in such species can also interfere with the reproduction of breeding pairs. Seychelles magpie robins, Copsychus sechellarum, live in social groups where subordinate individuals do not breed. Analysis of long-term individual-based data and short-term behavioural observations show that subordinates increase the territorial takeover frequency of established breeders. Such takeovers delay offspring production and decrease territory productivity. Individual-based simulations of the Seychelles magpie robin population parameterized with the long-term data show that this process has significantly postponed the recovery of the species from the Critically Endangered status. Social conflict thus can extend the period of high extinction risk, which we show to have population consequences that should be taken into account in management programmes. This is the first quantitative assessment of the effects of social conflict on conservation.

Adaptation and yield of pigeonpea in different environments in Tanzania

Pigeonpea is grown in wide range of cropping systems and environments, both in East Africa and internationally. An important feature of adaptation to these diverse systems and environments is the timing of flowering and maturity. Most traditional cultivars grown in Tanzania are medium to late flowering types (> 150 days), although extra-early flowering cultivars are now available. The aim of the present investigation was to measure biomass (BY) and seed (SY) yield of a set of phenologically diverse cultivars to determine their adaptation to contrasting environments in Tanzania. Ten cultivars, from extra-early (60 days) to late (> 180 days) flowering, were planted at six locations varying in mean temperature, photoperiod and rainfall. Days to flowering (DTF) and maturity, and above-ground BY and SY at maturity, were measured. A stress index (ETr:ETm ratio, 100 = no stress) was computed for each site. Rainfall and the stress index at the different sites varied from 322 to 1297 mm and 57 to 89, respectively. Among cultivars, DTF varied from 55 to 320 days, the stress index from 3 to 98, BY from 700 to 25,000 kg ha(-1), and SY from 0 to 4000 kg ha(-1). The highest yielding environment was at Selian, where mean temperatures were favourable (19 degrees C) and no stress occurred. At all sites there was an optimum DTF, which for SY varied from < 100 to 150 days. The best adapted cultivars were ICP 7035, ICPL 90094, Kat 50 and QP37, which were all medium flowering (c. 150 day) types. Extra-early cultivars such as ICPL 86005 also showed considerable potential, especially in short-season environments. (c) 2004 Elsevier B.V. All rights reserved.

Effects of summer rainfall manipulations on the abundance and vertical distribution of herbivorous soil macro-invertebrates

Soil invertebrate communities are likely to be highly vulnerable to low soil moisture, caused by a reduction in summer rainfall which is predicted for some regions under current climate change scenarios. However, the effects of changes in summer rainfall on soil invertebrate assemblages have rarely been tested experimentally. In this study, samples were taken in 2003 and 2004 from a long-running field experiment, to investigate the impact of 10 years of experimental summer drought and increased summer rainfall manipulations on the soil fauna of a calcareous grassland. Summer drought altered the soil invertebrate assemblage in the autumn, immediately following treatment application, but by the following spring treatment effects were no longer apparent. The two most common root herbivore species responded differently to the summer rainfall manipulations. Larvae of the dominant root-chewing species, Agriotes lineatus, were more numerous under enhanced rainfall in both the spring and autumn. In contrast, abundance of the Coccoidea Lecanopsis formicarum was unaffected by the rainfall manipulations. The responses of root herbivores to an increased incidence of summer droughts are therefore likely to vary, depending on their feeding strategy and life history. (c) 2007 Elsevier Masson SAS. All rights reserved.

Food crops in a changing climate

Changes in both the mean and the variability of climate, whether naturally forced, or due to human activities, pose a threat to crop production globally. This paper summarizes discussions of this issue at a meeting of the Royal Society in April 2005. Recent advances in understanding the sensitivity of crops to weather, climate and the levels of particular gases in the atmosphere indicate that the impact of these factors on crop yields and quality may be more severe than previously thought. There is increasing information on the importance to crop yields of extremes of temperature and rainfall at key stages of crop development. Agriculture will itself impact on the climate system and a greater understanding of these feedbacks is needed. Complex models are required to perform simulations of climate variability and change, together with predictions of how crops will respond to different climate variables. Variability of climate, such as that associated with El Niño events, has large impacts on crop production. If skilful predictions of the probability of such events occurring can be made a season or more in advance, then agricultural and other societal responses can be made. The development of strategies to adapt to variations in the current climate may also build resilience to changes in future climate. Africa will be the part of the world that is most vulnerable to climate variability and change, but knowledge of how to use climate information and the regional impacts of climate variability and change in Africa is rudimentary. In order to develop appropriate adaptation strategies globally, predictions about changes in the quantity and quality of food crops need to be considered in the context of the entire food chain from production to distribution, access and utilization. Recommendations for future research priorities are given.

A novel variant on chromosome 7q22.3 associated with mean platelet volume, counts, and function

Mean platelet volume (MPV) and platelet count (PLT) are highly heritable and tightly regulated traits. We performed a genome-wide association study for MPV and identified one SNP, rs342293, as having highly significant and reproducible association with MPV (per-G allele effect 0.016 +/- 0.001 log fL; P < 1.08 x 10(-24)) and PLT (per-G effect -4.55 +/- 0.80 10(9)/L; P < 7.19 x 10(-8)) in 8586 healthy subjects. Whole-genome expression analysis in the 1-MB region showed a significant association with platelet transcript levels for PIK3CG (n = 35; P = .047). The G allele at rs342293 was also associated with decreased binding of annexin V to platelets activated with collagen-related peptide (n = 84; P = .003). The region 7q22.3 identifies the first QTL influencing platelet volume, counts, and function in healthy subjects. Notably, the association signal maps to a chromosome region implicated in myeloid malignancies, indicating this site as an important regulatory site for hematopoiesis. The identification of loci regulating MPV by this and other studies will increase our insight in the processes of megakaryopoiesis and proplatelet formation, and it may aid the identification of genes that are somatically mutated in essential thrombocytosis. (Blood. 2009; 113: 3831-3837)

Mechanisms and function of flower and inflorescence reversion

Flower and inflorescence reversion involve a switch from floral development back to vegetative development, thus rendering flowering a phase in an ongoing growth pattern rather than a terminal act of the meristem. Although it can be considered an unusual event, reversion raises questions about the nature and function of flowering. It is linked to environmental conditions and is most often a response to conditions opposite to those that induce flowering. Research on molecular genetic mechanisms underlying plant development over the last 15 years has pinpointed some of the key genes involved in the transition to flowering and flower development. Such investigations have also uncovered mutations which reduce floral maintenance or alter the balance between vegetative and floral features of the plant. How this information contributes to an understanding of floral reversion is assessed here. One issue that arises is whether floral commitment (defined as the ability to continue flowering when inductive conditions no longer exist) is a developmental switch affecting the whole plant or is a mechanism which assigns autonomy to individual meristems. A related question is whether floral or vegetative development is the underlying default pathway of the plant. This review begins by considering how studies of flowering in Arabidopsis thaliana have aided understanding of mechanisms of floral maintenance. Arabidopsis has not been found to revert to leaf production in any of the conditions or genetic backgrounds analysed to date. A clear-cut reversion to leaf production has, however, been described in Impatiens balsamina. It is proposed that a single gene controls whether Impatiens reverts or can maintain flowering when inductive conditions are removed, and it is inferred that this gene functions to control the synthesis or transport of a leaf-generated signal. But it is also argued that the susceptibility of Impatiens to reversion is a consequence of the meristem-based mechanisms controlling development of the flower in this species. Thus, in Impatiens, a leaf-derived signal is critical for completion of flowering and can be considered to be the basis of a plant-wide floral commitment that is achieved without accompanying meristem autonomy. The evidence, derived from in vitro and other studies, that similar mechanisms operate in other species is assessed. It is concluded that most species (including Arabidopsis) are less prone to reversion because signals from the leaf are less ephemeral, and the pathways driving flower development have a high level of redundancy that generates meristem autonomy even when leaf-derived signals are weak. This gives stability to the flowering process, even where its initiation is dependent on environmental cues. On this interpretation, Impatiens reversion appears as an anomaly resulting from an unusual combination of leaf signalling and meristem regulation. Nevertheless, it is shown that the ability to revert can serve a function in the life history strategy (perenniality) or reproductive habit (pseudovivipary) of many plants. In these instances reversion has been assimilated into regular plant development and plays a crucial role there.

A theoretical adaptive model of thermal comfort – Adaptive Predicted Mean Vote (aPMV)

This paper presents in detail a theoretical adaptive model of thermal comfort based on the “Black Box” theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient (λ) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results.