On the uncertainty and confidence in decision support tools (DSTs) with insights from the Baltic Sea ecosystem

Ecosystems around the world are increasingly exposed to multiple, often interacting human activities, leading to pressures and possibly environmental state changes. Decision support tools (DSTs) can assist environmental managers and policy makers to evaluate the current status of ecosystems (i.e. assessment tools) and the consequences of alternative policies or management scenarios (i.e. planning tools) to make the best possible decision based on prevailing knowledge and uncertainties. However, to be confident in DST outcomes it is imperative that known sources of uncertainty such as sampling and measurement error, model structure, and parameter use are quantified, documented, and addressed throughout the DST set-up, calibration, and validation processes. Here we provide a brief overview of the main sources of uncertainty and methods currently available to quantify uncertainty in DST input and output. We then review 42 existing DSTs that were designed to manage anthropogenic pressures in the Baltic Sea to summarise how and what sources of uncertainties were addressed within planning and assessment tools. Based on our findings, we recommend future DST development to adhere to good modelling practise principles, and to better document and communicate uncertainty among stakeholders.Electronic supplementary materialThe online version of this article (doi:10.1007/s13280-020-01385-x) contains supplementary material, which is available to authorized users.     

Current practice of first-trimester ultrasound screening for structural fetal anomalies in developed countries

Objectives

First-trimester ultrasound screening is increasingly performed to detect fetal anomalies early in pregnancy, aiming to enhance reproductive autonomy for future parents. This study aims to display the current practice of first-trimester ultrasound screening in developed countries.

Method

An online survey among 47 prenatal screening experts in developed countries.

Results

First-trimester structural anomaly screening is available in 30 of the 33 countries and is mostly offered to all women with generally high uptakes. National protocols are available in 23/30 (76.7%) countries, but the extent of anatomy assessment varies. Monitoring of scan quality occurs in 43.3% of the countries. 23/43 (53.5%) of the respondents considered the quality of first-trimester ultrasound screening unequal in different regions of their country.

Conclusions

First-trimester screening for structural fetal anomalies is widely offered in developed countries, but large differences are reported in availability and use of screening protocols, the extent of anatomy assessment, training and experience of sonographers and quality monitoring systems. Consequently, this results in an unequal offer to parents in developed countries, sometimes even within the same country. Furthermore, as offer and execution differ widely, this has to be taken into account when results of screening policies are scientifically published or compared.     

All-in-one whole exome sequencing strategy with simultaneous copy number variant,single nucleotide variant and absence-of-heterozygosity analysis in fetuses with structural ultrasound anomalies: A 1-year experience

Objective

We performed a 1-year evaluation of a novel strategy of simultaneously analyzing single nucleotide variants (SNVs), copy number variants (CNVs) and copy-number-neutral Absence-of-Heterozygosity from Whole Exome Sequencing (WES) data for prenatal diagnosis of fetuses with ultrasound (US) anomalies and a non-causative QF-PCR result.

Methods

After invasive diagnostics, whole exome parent-offspring trio-sequencing with exome-wide CNV analysis was performed in pregnancies with fetal US anomalies and a non-causative QF-PCR result (WES-CNV). On request, additional SNV-analysis, restricted to (the) requested gene panel(s) only (with the option of whole exome SNV-analysis afterward) was performed simultaneously (WES-CNV/SNV) or as rapid SNV-re-analysis, following a normal CNV analysis.

Results

In total, 415 prenatal samples were included. Following a non-causative QF-PCR result, WES-CNV analysis was initially requested for 74.3% of the chorionic villus (CV) samples and 45% of the amniotic fluid (AF) samples. In case WES-CNV analysis did not reveal a causative aberration, SNV-re-analysis was requested in 41.7% of the CV samples and 17.5% of the AF samples. All initial analyses could be finished within 2 weeks after sampling. For SNV-re-analysis during pregnancy, turn-around-times (TATs) varied between one and 8 days.

Conclusion

We show a highly efficient all-in-one WES-based strategy, with short TATs, and the option of rapid SNV-re-analysis after a normal CNV result.     

Birthweight of children with isolated congenital heart disease—A sibling analysis study

Objective

Congenital heart disease (CHD) is associated with decreased birthweight (BW) compared to population-based references. The aim of this study was to compare the BW of isolated CHD cases to their siblings, thus controlling for unknown and unmeasured confounders within the family.

Methods

All isolated CHD cases in the Leiden University Medical Center were included (2002–2019). Generalized estimated equation models were constructed to compare BW z scores of CHD neonates with their siblings. Cases were clustered to minor or severe CHD and stratified according to the aortic flow and oxygenation to the brain.

Results

The overall BW z score of siblings was 0.032 (n = 471). The BW z score was significantly lower in CHD cases (n = 291) compared to their siblings (−0.20, p = 0.005). The results were consistent in the subgroup analysis of severe and minor CHD (BW z score difference −0.20 and −0.10), but did not differ significantly (p = 0.63). Stratified analysis regarding flow and oxygenation showed no BW difference between the groups (p = 0.1).

Conclusion

Isolated CHD cases display a significantly lower BW z score compared to their siblings. As the siblings of these CHD cases show a BW distribution similar to the general population, this suggests that shared environmental and maternal influences between siblings do not explain the difference in BW.     

Perinatal outcome after selective fetal reduction in monochorionic twin pregnancies: A comparison of techniques over a 20-year period

Objective

To assess the perinatal outcome after fetal reduction in complicated monochorionic (MC) twin pregnancies by comparing different techniques.

Methods

A retrospective cohort study at a national referral center comparing data between four techniques: interstitial laser coagulation, radiofrequency ablation (RFA), fetoscopic laser coagulation (FLC) and bipolar cord coagulation (BCC). The primary outcome was the mortality of the co-twins. Secondary outcomes were preterm pre-labor rupture of membranes (PPROM), gestational age at delivery and neonatal morbidity.

Results

259 MC twin pregnancies underwent selective fetal reduction: 29 IL, 64 RFA, 85 FLC and 81 BCC. The perinatal mortality rate was 29% and fetal demise of the co-twins occurred in 19%. The lowest mortality rate was seen after BCC (17%, p = 0.012). PPROM occurred in 18% patients without significant differences between techniques. The mean gestational age at delivery in liveborn children was 35 weeks and did not differ between techniques. Severe cerebral injury and neonatal morbidity were reported in 4% and 14%, respectively, without significant differences between techniques.

Conclusions

Selective fetal reductions in MC twins are precarious procedures with an increased risk of perinatal mortality of the co-twins. Our results show the lowest mortality rates after BCC. However, high PPROM rates were seen irrespective of the technique.     

Spatial and Seasonal Variation of Dissolved Organic Carbon (DOC) Concentrations in Irish Streams: Importance of Soil and Topography Characteristics

Dissolved organic carbon (DOC) concentrations have increased in many sites in Europe and North America in recent decades. High DOC concentrations can damage the structure and functions of aquatic ecosystems by influencing water chemistry. This study investigated the spatial and seasonal variation of DOC concentrations in Irish streams across 55 sites at seven time occasions over 1 year (2006/2007). The DOC concentrations ranged from 0.9 to 25.9 mg/L with a mean value of 6.8 and a median value of 5.7 mg/L and varied significantly over the course of the year. The DOC concentrations from late winter (February: 5.2 ± 3.0 mg/L across 55 sites) and early spring (April: 4.5 ± 3.5 mg/L) had significantly lower DOC concentrations than autumn (October: mean 8.3 ± 5.6 mg/L) and early winter (December: 8.3 ± 5.1 mg/L). The DOC production sources (e.g., litterfall) or the accumulation of DOC over dry periods might be the driving factor of seasonal change in Irish stream DOC concentrations. Analysis of data using stepwise multiple linear regression techniques identified the topographic index (TI, an indication of saturation-excess runoff potential) and soil conditions (organic carbon content and soil drainage characteristics) as key factors in controlling DOC spatial variation in different seasons. The TI and soil carbon content (e.g., soil organic carbon; peat occurrence) are positively related to DOC concentrations, while well-drained soils are negatively related to DOC concentrations. The knowledge of spatial and seasonal variation of DOC concentrations in streams and their drivers are essential for optimum riverine water resources management.     

Greenhouse gas emissions along a peat swamp forest degradation gradient in the Peruvian Amazon: soil moisture and palm roots effects

Tropical peatlands in the Peruvian Amazon exhibit high densities of Mauritia flexuosa palms, which are often cut instead of being climbed for collecting their fruits. This is an important type of forest degradation in the region that could lead to changes in the structure and composition of the forest, quality and quantity of inputs to the peat, soil properties, and greenhouse gas (GHG) fluxes. We studied peat and litterfall characteristics along a forest degradation gradient that included an intact site, a moderately degraded site, and a heavily degraded site. To understand underlying factors driving GHG emissions, we examined the response of in vitro soil microbial GHG emissions to soil moisture variation, and we tested the potential of pneumatophores to conduct GHGs in situ. The soil phosphorus and carbon content and carbon-to-nitrogen ratio as well as the litterfall nitrogen content and carbon-to-nitrogen ratio were significantly affected by forest degradation. Soils from the degraded sites consistently produced more carbon dioxide (CO₂) than soils from the intact site during in vitro incubations. The response of CO₂ production to changes in water-filled pore space (WFPS) followed a cubic polynomial relationship with maxima at 60–70% at the three sites. Methane (CH₄) was produced in limited amounts and exclusively under water-saturated conditions. There was no significant response of nitrous oxide (N₂O) emissions to WFPS variation. Lastly, the density of pneumatophore decreased drastically as the result of forest degradation and was positively correlated to in situ CH₄ emissions. We conclude that recurrent M. flexuosa harvesting could result in a significant increase of in situ CO₂ fluxes and a simultaneous decrease in CH₄ emissions via pneumatophores. These changes might alter long-term carbon and GHG balances of the peat, and the role of these ecosystems for climate change mitigation, which stresses the need for their protection.

     

Chloramine demand estimation using surrogate chemical and microbiological parameters

A model is developed to enable estimation of chloramine demand in full scale drinking water supplies based on chemical and microbiological factors that affect chloramine decay rate via nonlinear regression analysis method. The model is based on organic character (specific ultraviolet absorbance (SUVA)) of the water samples and a laboratory measure of the microbiological (F m ) decay of chloramine. The applicability of the model for estimation of chloramine residual (and hence chloramine demand) was tested on several waters from different water treatment plants in Australia through statistical test analysis between the experimental and predicted data. Results showed that the model was able to simulate and estimate chloramine demand at various times in real drinking water systems. To elucidate the loss of chloramine over the wide variation of water quality used in this study, the model incorporates both the fast and slow chloramine decay pathways. The significance of estimated fast and slow decay rate constants as the kinetic parameters of the model for three water sources in Australia was discussed. It was found that with the same water source, the kinetic parameters remain the same. This modelling approach has the potential to be used by water treatment operators as a decision support tool in order to manage chloramine disinfection.     

Economic analysis of adaptive strategies for flood risk management under climate change

Climate change requires reconsideration of flood risk management strategies. Cost-benefit analysis (CBA), an economic decision-support tool, has been widely applied to assess these strategies. This paper aims to describe and discuss probabilistic extensions of CBA to identify welfare-maximising flood risk management strategies under climate change. First, uncertainty about the changes in return periods of hydro-meteorological extremes is introduced by probability-weighted climate scenarios. Second, the analysis is extended by learning about climate change impacts. Learning occurs upon the probabilistic arrival of information. We distinguish between learning from scientific progress, from statistical evidence and from flood disasters. These probabilistic extensions can be used to analyse and compare the economic efficiency and flexibility of flood risk management strategies under climate change. We offer a critical discussion of the scope of such extensions and options for increasing flexibility. We find that uncertainty reduction from scientific progress may reduce initial investments, while other types of learning may increase initial investments. This requires analysing effects of different types of learning. We also find that probabilistic information about climate change impacts and learning is imprecise. We conclude that risk-based CBA with learning improves the flexibility of flood risk management strategies under climate change. However, CBA provides subjective estimates of expected outcomes and reflects different decision-maker preferences than those captured in robustness analyses. We therefore advocate robustness analysis in addition to, or combined with, cost-benefit analysis to support local investment decisions on flood risk reduction and global strategies on allocation of adaptation funds for flood risk management.