Prediction and uncertainty source analysis of the spatial and temporal disturbance from off-road vehicular traffic in a complex ecosystem

Vehicle use during military training activities results in soil disturbance and vegetation loss. The capacity of lands to sustain training is a function of the sensitivity of lands to vehicle use and the pattern of land use. The sensitivity of land to vehicle use has been extensively studied. Less well understood are the spatial patterns of vehicle disturbance. Since disturbance from off-road vehicular traffic moving through complex landscapes varies spatially, a spatially explicit nonlinear regression model (disturbance model) was used to predict the pattern of vehicle disturbance across a training facility. An uncertainty analysis of the model predictions assessed the spatial distribution of prediction uncertainty and the contribution of different error sources to that uncertainty.For the most part, this analysis showed that mapping and modeling process errors contributed more than 95% of the total uncertainty of predicted disturbance, while satellite imagery error contributed less than 5% of the uncertainty. When the total uncertainty was larger than a threshold, modeling error contributed 60% to 90% of the prediction uncertainty. Otherwise, mapping error contributed about 10% to 50% of the total uncertainty. These uncertainty sources were further partitioned spatially based on other sources of uncertainties associated with vehicle moment, landscape characterization, satellite imagery, etc.     

Fine-scale observations of the predatory behaviour of the carnivorous copepod <Emphasis Type="Italic">Paraeuchaeta norvegica</Emphasis> and the escape responses of their ichthyoplankton prey,Atlantic cod (<Emphasis Type="Italic">Gadus morhua</Emphasis>)

Paraeuchaeta norvegica (8.5 mm total length) and yolk-sac stage Atlantic cod larvae (4 mm total length) (Gadus morhua) larvae were observed in aquaria (3 l of water) using silhouette video photography. This allowed direct observations (and quantitative measurement) of predator–prey interactions between these two species in 3-dimensions. Tail beats, used by cod larvae to propel themselves through the viscous fluid environment, also generate signals detectable by mechanoreceptive copepod predators. When the prey is close enough for detection and successful capture (approximately half a body-length), the copepod launches an extremely rapid high Reynolds number attack, grabbing the larva around its midsection. While capture itself takes place in milliseconds, minutes are required to subdue and completely ingest a cod larva. The behavioural observations are used to estimate the hydrodynamic signal strength of the cod larva’s tail beats and the copepod’s perceptive field for larval fish prey. Cod larvae are more sensitive to fluid velocity than P. norvegica and also appear capable of distinguishing between the signal generated by a swimming and an attacking copepod. However, the copepod can lunge at much faster velocities than a yolk-sac cod larva can escape, leading to the larva’s capture. These observations can serve as input to the predator–prey component of ecosystem models intended to assess the impact of P. norvegica on cod larvae.     

Plant-trait-based modeling assessment of ecosystem-service sensitivity to land-use change

Evidence is accumulating that the continued provision of essential ecosystem services is vulnerable to land-use change. Yet, we lack a strong scientific basis for this vulnerability as the processes that drive ecosystem-service delivery often remain unclear. In this paper, we use plant traits to assess ecosystem-service sensitivity to land-use change in subalpine grasslands. We use a trait-based plant classification (plant functional types, PFTs) in a landscape modeling platform to model community dynamics under contrasting but internally consistent land-use change scenarios. We then use predictive models of relevant ecosystem attributes, based on quantitative plant traits, to make projections of ecosystem-service delivery. We show that plant traits and PFTs are effective predictors of relevant ecosystem attributes for a range of ecosystem services including provisioning (fodder), cultural (land stewardship), regulating (landslide and avalanche risk), and supporting services (plant diversity). By analyzing the relative effects of the physical environment and land use on relevant ecosystem attributes, we also show that these ecosystem services are most sensitive to changes in grassland management, supporting current agri-environmental policies aimed at maintaining mowing of subalpine grasslands in Europe.     

The origins of aneuploidy research consortium

The presence of high levels of aneuploidy in oocytes and early embryos and their fate is of considerable scientific and clinical importance. The Origins of Aneuploidy Research Consortium (OARC) was established to promote interdisciplinary communication and collaborative research into this topic. Under the umbrella of OARC, a series of papers has now been published in this Special Issue of Prenatal Diagnosis. Recent studies have transformed the view that aneuploidy is usually attributable to meiotic non-disjunction. The molecular basis for the association between meiotic error and maternal age is becoming understood. The clinical significance of mitotic instability in the earliest cells divisions of the embryo is also becoming clearer. An error in the segregation of one or more whole chromosomes from a parent does not invariably result in a non-viable pregnancy or an abnormal outcome. Epidemiologic data allows an assessment of in utero viability, the effect of maternal age, and secondary factors that may affect aneuploidy prevalence. We advocate careful use of nomenclature and revision of educational materials to more accurately explain the complex and often nuanced mechanisms. OARC plans to hold additional workshops, promote additional publications and offer educational resources.     

Determining gestational age using genome methylation profile: A novel approach for fetal medicine

Gestational age determination by traditional tools (last menstrual period, ultrasonography measurements and Ballard Maturational Assessment in newborns) has major limitations and therefore there is a need to find different approaches. In this study, we looked for a molecular marker that can be used to determine the accurate gestational age of the newborn. To this end, we performed reduced representation bisulfite sequencing (RRBS) on 41 cord blood and matching placenta samples from women between 25 and 40 weeks of gestation and generated an epigenetic clock based on the methylation level at different loci in the genome. We identified a set of 332 differentially methylated regions (DMRs) that undergo demethylation in late gestational age in cord blood cells and can predict the gestational age (r = −.7, P = 2E-05). Once the set of 411 DMRs that undergo de novo methylation in late gestational age was used in combination with the first set, it generated a more accurate clock (R = .77, P = 1.87E-05). We have compared gestational age determined by Ballard score assessment with our epigenetic clock and found high concordance. Taken together, this study demonstrates that DNA methylation can accurately predict gestational age and thus may serve as a good clinical predictor.