The transcriptome of Populus in elevated CO2

The consequences of increasing atmospheric carbon dioxide for long-term adaptation of forest ecosystems remain uncertain, with virtually no studies undertaken at the genetic level. A global analysis using cDNA microarrays was conducted following 6 yr exposure of Populus × euramericana (clone I-214) to elevated [CO2] in a FACE (free-air CO2 enrichment) experiment.• Gene expression was sensitive to elevated [CO2] but the response depended on the developmental age of the leaves, and < 50 transcripts differed significantly between different CO2 environments. For young leaves most differentially expressed genes were upregulated in elevated [CO2], while in semimature leaves most were downregulated in elevated [CO2].• For transcripts related only to the small subunit of Rubisco, upregulation in LPI 3 and downregulation in LPI 6 leaves in elevated CO2 was confirmed by anova. Similar patterns of gene expression for young leaves were also confirmed independently across year 3 and year 6 microarray data, and using real-time RT–PCR.• This study provides the first clues to the long-term genetic expression changes that may occur during long-term plant response to elevated CO2.

The effect of environmental change on human migration

The influence of the environment and environmental change is largely unrepresented in standard theories of migration, whilst recent debates on climate change and migration focus almost entirely on displacement and perceive migration to be a problem. Drawing on an increasing evidence base that has assessed elements of the influence of the environment on migration, this paper presents a new framework for understanding the effect of environmental change on migration. The framework identifies five families of drivers which affect migration decisions: economic, political, social, demographic and environmental drivers. The environment drives migration through mechanisms characterised as the availability and reliability of ecosystem services and exposure to hazard. Individual migration decisions and flows are affected by these drivers operating in combination, and the effect of the environment is therefore highly dependent on economic, political, social and demographic context. Environmental change has the potential to affect directly the hazardousness of place. Environmental change also affects migration indirectly, in particular through economic drivers, by changing livelihoods for example, and political drivers, through affecting conflicts over resources, for example. The proposed framework, applicable to both international and internal migration, emphasises the role of human agency in migration decisions, in particular the linked role of family and household characteristics on the one hand, and barriers and facilitators to movement on the other in translating drivers into actions. The framework can be used to guide new research, assist with the evaluation of policy options, and provide a context for the development of scenarios representing a range of plausible migration futures.

Migration and global environmental change

Introduction to a special issue on migration and global environmental change

Large is fast, small is tight: determinants of speed and affinity in subunit capture by a periplasmic chaperone

The chaperone/usher pathway assembles surface virulence organelles of Gram-negative bacteria, consisting of fibers of linearly polymerized protein subunits. Fiber subunits are connected through 'donor strand complementation': each subunit completes the immunoglobulin (Ig)-like fold of the neighboring subunit by donating the seventh β-strand in trans. Whereas the folding of Ig domains is a fast first-order process, folding of Ig modules into the fiber conformation is a slow second-order process. Periplasmic chaperones separate this process in two parts by forming transient complexes with subunits. Interactions between chaperones and subunits are also based on the principle of donor strand complementation. In this study, we have performed mutagenesis of the binding motifs of the Caf1M chaperone and Caf1 capsular subunit from Yersinia pestis and analyzed the effect of the mutations on the structure, stability, and kinetics of Caf1M-Caf1 and Caf1-Caf1 interactions. The results suggest that a large hydrophobic effect combined with extensive main-chain hydrogen bonding enables Caf1M to rapidly bind an early folding intermediate of Caf1 and direct its partial folding. The switch from the Caf1M-Caf1 contact to the less hydrophobic, but considerably tighter and less dynamic Caf1-Caf1 contact occurs via the zip-out-zip-in donor strand exchange pathway with pocket 5 acting as the initiation site. Based on these findings, Caf1M was engineered to bind Caf1 faster, tighter, or both faster and tighter. To our knowledge, this is the first successful attempt to rationally design an assembly chaperone with improved chaperone function.

Comment on ``Conditional Exceedance Probabilities''

In a recent paper, Mason et al. propose a reliability test of ensemble forecasts for a continuous, scalar verification. As noted in the paper, the test relies on a very specific interpretation of ensembles, namely, that the ensemble members represent quantiles of some underlying distribution. This quantile interpretation is not the only interpretation of ensembles, another popular one being the Monte Carlo interpretation. Mason et al. suggest estimating the quantiles in this situation; however, this approach is fundamentally flawed. Errors in the quantile estimates are not independent of the exceedance events, and consequently the conditional exceedance probabilities (CEP) curves are not constant, which is a fundamental assumption of the test. The test would reject reliable forecasts with probability much higher than the test size.

Predicting outliers in ensemble forecasts

An ensemble forecast is a collection of runs of a numerical dynamical model, initialized with perturbed initial conditions. In modern weather prediction for example, ensembles are used to retrieve probabilistic information about future weather conditions. In this contribution, we are concerned with ensemble forecasts of a scalar quantity (say, the temperature at a specific location). We consider the event that the verification is smaller than the smallest, or larger than the largest ensemble member. We call these events outliers. If a K-member ensemble accurately reflected the variability of the verification, outliers should occur with a base rate of 2/(K + 1). In operational forecast ensembles though, this frequency is often found to be higher. We study the predictability of outliers and find that, exploiting information available from the ensemble, forecast probabilities for outlier events can be calculated which are more skilful than the unconditional base rate. We prove this analytically for statistically consistent forecast ensembles. Further, the analytical results are compared to the predictability of outliers in an operational forecast ensemble by means of model output statistics. We find the analytical and empirical results to agree both qualitatively and quantitatively.

Allosteric mechanism controls traffic in the chaperone/usher pathway

Many virulence organelles of Gram-negative bacterial pathogens are assembled via the chaperone/ usher pathway. The chaperone transports organelle subunits across the periplasm to the outer membrane usher, where they are released and incorporated into growing fibers. Here, we elucidate the mechanism of the usher-targeting step in assembly of the Yersinia pestis F1 capsule at the atomic level. The usher interacts almost exclusively with the chaperone in the chaperone:subunit complex. In free chaperone, a pair of conserved proline residues at the beginning of the subunit-binding loop form a ‘‘proline lock’’ that occludes the usher-binding surface and blocks usher binding. Binding of the subunit to the chaperone rotates the proline lock away from the usher-binding surface, allowing the chaperone-subunit complex to bind to the usher. We show that the proline lock exists in other chaperone/usher systems and represents a general allosteric mechanism for selective targeting of chaperone:subunit complexes to the usher and for release and recycling of the free chaperone.

Rank histograms of stratified Monte-Carlo ensembles

The application of forecast ensembles to probabilistic weather prediction has spurred considerable interest in their evaluation. Such ensembles are commonly interpreted as Monte Carlo ensembles meaning that the ensemble members are perceived as random draws from a distribution. Under this interpretation, a reasonable property to ask for is statistical consistency, which demands that the ensemble members and the verification behave like draws from the same distribution. A widely used technique to assess statistical consistency of a historical dataset is the rank histogram, which uses as a criterion the number of times that the verification falls between pairs of members of the ordered ensemble. Ensemble evaluation is rendered more specific by stratification, which means that ensembles that satisfy a certain condition (e.g., a certain meteorological regime) are evaluated separately. Fundamental relationships between Monte Carlo ensembles, their rank histograms, and random sampling from the probability simplex according to the Dirichlet distribution are pointed out. Furthermore, the possible benefits and complications of ensemble stratification are discussed. The main conclusion is that a stratified Monte Carlo ensemble might appear inconsistent with the verification even though the original (unstratified) ensemble is consistent. The apparent inconsistency is merely a result of stratification. Stratified rank histograms are thus not necessarily flat. This result is demonstrated by perfect ensemble simulations and supplemented by mathematical arguments. Possible methods to avoid or remove artifacts that stratification induces in the rank histogram are suggested.

Numerical study of a M-cycle cross-flow heat exchanger for indirect evaporative cooling

In this paper, numerical analyses of the thermal performance of an indirect evaporative air cooler incorporating a M-cycle cross-flow heat exchanger has been carried out. The numerical model was established from solving the coupled governing equations for heat and mass transfer between the product and working air, using the finite-element method. The model was developed using the EES (Engineering Equation Solver) environment and validated by published experimental data. Correlation between the cooling (wet-bulb) effectiveness, system COP and a number of air flow/exchanger parameters was developed. It is found that lower channel air velocity, lower inlet air relative humidity, and higher working-to-product air ratio yielded higher cooling effectiveness. The recommended average air velocities in dry and wet channels should not be greater than 1.77 m/s and 0.7 m/s, respectively. The optimum flow ratio of working-to-product air for this cooler is 50%. The channel geometric sizes, i.e. channel length and height, also impose significant impact to system performance. Longer channel length and smaller channel height contribute to increase of the system cooling effectiveness but lead to reduced system COP. The recommend channel height is 4 mm and the dimensionless channel length, i.e., ratio of the channel length to height, should be in the range 100 to 300. Numerical study results indicated that this new type of M-cycle heat and mass exchanger can achieve 16.7% higher cooling effectiveness compared with the conventional cross-flow heat and mass exchanger for the indirect evaporative cooler. The model of this kind is new and not yet reported in literatures. The results of the study help with design and performance analyses of such a new type of indirect evaporative air cooler, and in further, help increasing market rating of the technology within building air conditioning sector, which is currently dominated by the conventional compression refrigeration technology.