Variational calculations of rovibrational states: a precise high-energy potential surface for HCN [and discussion]

We report the results of variational calculations of the rovibrational energy levels of HCN for J = 0, 1 and 2, where we reproduce all the ca. 100 observed vibrational states for all observed isotopic species, with energies up to 18000 cm$^{-1}$, to about $\pm $1 cm$^{-1}$, and the corresponding rotational constants to about $\pm $0.001 cm$^{-1}$. We use a hamiltonian expressed in internal coordinates r$_{1}$, r$_{2}$ and $\theta $, using the exact expression for the kinetic energy operator T obtained by direct transformation from the cartesian representation. The potential energy V is expressed as a polynomial expansion in the Morse coordinates y$_{i}$ for the bond stretches and the interbond angle $\theta $. The basis functions are built as products of appropriately scaled Morse functions in the bond-stretches and Legendre or associated Legendre polynomials of cos $\theta $ in the angle bend, and we evaluate matrix elements by Gauss quadrature. The hamiltonian matripx is factorized using the full rovibrational symmetry, and the basis is contracted to an optimized form; the dimensions of the final hamiltonian matrix vary from 240 $\times $ 240 to 1000 $\times $ 1000.We believe that our calculation is converged to better than 1 cm$^{-1}$ at 18 000 cm$^{-1}$. Our potential surface is expressed in terms of 31 parameters, about half of which have been refined by least squares to optimize the fit to the experimental data. The advantages and disadvantages and the future potential of calculations of this type are discussed.

Evolutionary bi-stability in pathogen transmission mode

Many pathogens transmit to new hosts by both infection (horizontal transmission) and transfer to the infected host's offspring (vertical transmission). These two transmission modes require speci®c adap- tations of the pathogen that can be mutually exclusive, resulting in a trade-off between horizontal and vertical transmission. We show that in mathematical models such trade-offs can lead to the simultaneous existence of two evolutionary stable states (evolutionary bi-stability) of allocation of resources to the two modes of transmission. We also show that jumping between evolutionary stable states can be induced by gradual environmental changes. Using quantitative PCR-based estimates of abundance in seed and vege- tative parts, we show that the pathogen of wheat, Phaeosphaeria nodorum, has jumped between two distinct states of transmission mode twice in the past 160 years, which, based on published evidence, we interpret as adaptation to environmental change. The ®nding of evolutionary bi-stability has impli- cations for human, animal and other plant diseases. An ill-judged change in a disease control programme could cause the pathogen to evolve a new, and possibly more damaging, combination of transmission modes. Similarly, environmental changes can shift the balance between transmission modes, with adverse effects on human, animal and plant health.

Land plants and DNA barcodes: short-term and long-term goals

Land plants have had the reputation of being problematic for DNA barcoding for two general reasons: (i) the standard DNA regions used in algae, animals and fungi have exceedingly low levels of variability and (ii) the typically used land plant plastid phylogenetic markers (e.g. rbcL, trnL-F, etc.) appear to have too little variation. However, no one has assessed how well current phylogenetic resources might work in the context of identification (versus phylogeny reconstruction). In this paper, we make such an assessment, particularly with two of the markers commonly sequenced in land plant phylogenetic studies, plastid rbcL and internal transcribed spacers of the large subunits of nuclear ribosomal DNA (ITS), and find that both of these DNA regions perform well even though the data currently available in GenBank/EBI were not produced to be used as barcodes and BLAST searches are not an ideal tool for this purpose. These results bode well for the use of even more variable regions of plastid DNA (such as, for example, psbA-trnH) as barcodes, once they have been widely sequenced. In the short term, efforts to bring land plant barcoding up to the standards being used now in other organisms should make swift progress. There are two categories of DNA barcode users, scientists in fields other than taxonomy and taxonomists. For the former, the use of mitochondrial and plastid DNA, the two most easily assessed genomes, is at least in the short term a useful tool that permits them to get on with their studies, which depend on knowing roughly which species or species groups they are dealing with, but these same DNA regions have important drawbacks for use in taxonomic studies (i.e. studies designed to elucidate species limits). For these purposes, DNA markers from uniparentally (usually maternally) inherited genomes can only provide half of the story required to improve taxonomic standards being used in DNA barcoding. In the long term, we will need to develop more sophisticated barcoding tools, which would be multiple, low-copy nuclear markers with sufficient genetic variability and PCR-reliability; these would permit the detection of hybrids and permit researchers to identify the 'genetic gaps' that are useful in assessing species limits.

Water reuse for irrigated agriculture in Jordan: challenges of soil sustainability and the role of management strategies

Reclaimed water provides an important contribution to the water balance in water-scarce Jordan, but the quality of this water presents both benefits and challenges. Careful management of reclaimed water is required to maximize the nutrient benefits while minimizing the salinity risks. This work uses a multi-disciplinary research approach to show that soil response to irrigation with reclaimed water is a function of the management strategies adopted on the farm by the water user. The adoption of management methods to maintain soil productivity can be seen to be a result of farmers’ awareness to potentially plant-toxic ions in the irrigation water (70% of Jordan Valley farmers identified salinization as a hazard from irrigation with reclaimed water). However, the work also suggests that farmers’ management capacity is affected by the institutional management of water. About a third (35%) of farmers in the Jordan Valley claimed that their ability to manage salinization was limited by water shortages. Organizational interviews revealed that institutional awareness of soil management challenges was quite high (34% of interviewees described salinization as a risk from water reuse), but strategies to address this challenge at the institutional level require greater development.

Dynamical influences on European climate: an uncertain future

Climate science is coming under increasing pressure to deliver projections of future climate change at spatial scales as small as a few kilometres for use in impacts studies. But is our understanding and modelling of the climate system advanced enough to offer such predictions? Here we focus on the Atlantic–European sector, and on the effects of greenhouse gas forcing on the atmospheric and, to a lesser extent, oceanic circulations. We review the dynamical processes which shape European climate and then consider how each of these leads to uncertainty in the future climate. European climate is unique in many regards, and as such it poses a unique challenge for climate prediction. Future European climate must be considered particularly uncertain because (i) the spread between the predictions of current climate models is still considerable and (ii) Europe is particularly strongly affected by several processes which are known to be poorly represented in current models.

A model-based assessment of the effects of projected climate change on the water resources of Jordan

This paper is concerned with the quantification of the likely effect of anthropogenic climate change on the water resources of Jordan by the end of the twenty-first century. Specifically, a suite of hydrological models are used in conjunction with modelled outcomes from a regional climate model, HadRM3, and a weather generator to determine how future flows in the upper River Jordan and in the Wadi Faynan may change. The results indicate that groundwater will play an important role in the water security of the country as irrigation demands increase. Given future projections of reduced winter rainfall and increased near-surface air temperatures, the already low groundwater recharge will decrease further. Interestingly, the modelled discharge at the Wadi Faynan indicates that extreme flood flows will increase in magnitude, despite a decrease in the mean annual rainfall. Simulations projected no increase in flood magnitude in the upper River Jordan. Discussion focuses on the utility of the modelling framework, the problems of making quantitative forecasts and the implications of reduced water availability in Jordan.

Restricted dispersal reduces the strength of spatial density dependence in a tropical bird population

Spatial processes could play an important role in density-dependent population regulation because the disproportionate use of poor quality habitats as population size increases is widespread in animal populations-the so-called buffer effect. While the buffer effect patterns and their demographic consequences have been described in a number of wild populations, much less is known about how dispersal affects distribution patterns and ultimately density dependence. Here, we investigated the role of dispersal in spatial density dependence using an extraordinarily detailed dataset from a reintroduced Mauritius kestrel (Falco punctatus) population with a territorial (despotic) breeding system. We show that recruitment rates varied significantly between territories, and that territory occupancy was related to its recruitment rate, both of which are consistent with the buffer effect theory. However, we also show that restricted dispersal affects the patterns of territory occupancy with the territories close to release sites being occupied sooner and for longer as the population has grown than the territories further away. As a result of these dispersal patterns, the strength of spatial density dependence is significantly reduced. We conclude that restricted dispersal can modify spatial density dependence in the wild, which has implications for the way population dynamics are likely to be impacted by environmental change.

Quantifying uncertainty in the simulation of crop-climate processes

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Direct versus indirect sexual selection: genetic basis of colour, size and recruitment in a wild bird

Indirect and direct models of sexual selection make different predictions regarding the quantitative genetic relationships between sexual ornaments and fitness. Indirect models predict that ornaments should have a high heritability and that strong positive genetic covariance should exist between fitness and the ornament. Direct models, on the other hand, make no such assumptions about the level of genetic variance in fitness and the ornament, and are therefore likely to be more important when environmental sources of variation are large. Here we test these predictions in a wild population of the blue tit (Parus caeruleus), a species in which plumage coloration has been shown to be under sexual selection. Using 3 years of cross-fostering data from over 250 breeding attempts, we partition the covariance between parental coloration and aspects of nestling fitness into a genetic and environmental component. Contrary to indirect models of sexual selection, but in agreement with direct models, we show that variation in coloration is only weakly heritable (h(2) < 0.11), and that two components of offspring fitness-nestling size and fledgling recruitment-are strongly dependent on parental effects, rather than genetic effects. Furthermore, there was no evidence of significant positive genetic covariation between parental colour and offspring traits. Contrary to direct benefit models, however, we find little evidence that variation in colour reliably indicates the level of parental care provided by either males or females. Taken together, these results indicate that the assumptions of indirect models of sexual selection are not supported by the genetic basis of the traits reported on here.

Extinction processes in hotspots of avian biodiversity and the targeting of pre-emptive conservation action

Hot spots of endemism are regarded as important global sites for conservation as they are rich in threatened endemic species and currently experiencing extensive habitat loss. Targeting pre-emptive conservation action to sites that are currently relatively intact but which would be vulnerable to particular human activities if they occurred in the future is, however, also valuable but has received less attention. Here, we address this issue by using data on Endemic Bird Areas (EBAs). First, we identify the ecological factors that affect extinction risk in the face of particular human activities, and then use these insights to identify EBAs that should be priorities for pre-emptive conservation action. Threatened endemic species in EBAs are significantly more likely to be habitat specialists or relatively large-bodied than non-threatened species, when compared across avian families. Increasing habitat loss causes a significant increase in extinction risk among habitat specialists, but we found no evidence to suggest that the presence of alien species/human exploitation causes a significant increase in extinction risk among large-bodied species. This suggests that these particular human activities are contributing to high extinction risk among habitat specialists, but not among large-bodied species. Based on these analyses, we identify 39 EBAs containing 570 species (24% of the total in EBAs) that are not currently threatened with severe habitat loss, but would be ecologically vulnerable to future habitat loss should it occur. We show that these sites tend to be poorly represented in existing priority setting exercises involving hot spots, suggesting that vulnerability must be explicitly included within these exercises if such sites are to be adequately protected.

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.

Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo

The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon-known as heterotachy-can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify those branches in which reliable amounts of heterotachy occur. We implement the method in combination with our 'pattern-heterogeneity' mixture model, applying it to simulated data and five published datasets. We find that complex evolutionary signals of heterotachy are routinely present over and above variation in the rate or pattern of evolution across sites, that the reversible-jump method requires far fewer parameters than conventional mixture models to describe it, and serves to identify the regions of the tree in which heterotachy is most pronounced. The reversible-jump procedure also removes the need for a posteriori tests of 'significance' such as the Akaike or Bayesian information criterion tests, or Bayes factors. Heterotachy has important consequences for the correct reconstruction of phylogenies as well as for tests of hypotheses that rely on accurate branch-length information. These include molecular clocks, analyses of tempo and mode of evolution, comparative studies and ancestral state reconstruction. The model is available from the authors' website, and can be used for the analysis of both nucleotide and morphological data.