Climate warming shifts riverine macroinvertebrate communities to be more sensitive to chemical pollutants.

Freshwaters are highly threatened ecosystems that are vulnerable to chemical pollution and climate change. Freshwater taxa vary in their sensitivity to chemicals and changes in species composition can potentially affect the sensitivity of assemblages to chemical exposure. Here we explore the potential consequences of future climate change on the composition and sensitivity of freshwater macroinvertebrate assemblages to chemical stressors using the UK as a case study. Macroinvertebrate assemblages under end of century (2080-2100) and baseline (1980-2000) climate conditions were predicted for 608 UK sites for four climate scenarios corresponding to mean temperature changes of 1.28 to 3.78°C. Freshwater macroinvertebrate toxicity data were collated for 19 chemicals and the hierarchical species sensitivity distribution model was used to predict the sensitivity of untested taxa using relatedness within a Bayesian approach. All four future climate scenarios shifted assemblage compositions, increasing the prevalence of Mollusca, Crustacea and Oligochaeta species, and the insect taxa of Odonata, Chironomidae, and Baetidae species. Contrastingly, decreases were projected for Plecoptera, Ephemeroptera (except for Baetidae) and Coleoptera species. Shifts in taxonomic composition were associated with changes in the percentage of species at risk from chemical exposure. For the 3.78°C climate scenario, 76% of all assemblages became more sensitive to chemicals and for 18 of the 19 chemicals, the percentage of species at risk increased. Climate warming-induced increases in sensitivity were greatest for assemblages exposed to metals and were dependent on baseline assemblage composition, which varied spatially. Climate warming is predicted to result in changes in the use, environmental exposure and toxicity of chemicals. Here we show that, even in the absence of these climate-chemical interactions, shifts in species composition due to climate warming will increase chemical risk and that the impact of chemical pollution on freshwater macroinvertebrate biodiversity may double or quadruple by the end of the 21st century.

Cross-species extrapolation of chemical sensitivity.

Ecosystems are usually populated by many species. Each of these species carries the potential to show a different sensitivity towards all of the numerous chemical compounds that can be present in their environment. Since experimentally testing all possible species-chemical combinations is impossible, the ecological risk assessment of chemicals largely depends on cross-species extrapolation approaches. This review overviews currently existing cross-species extrapolation methodologies, and discusses i) how species sensitivity could be described, ii) which predictors might be useful for explaining differences in species sensitivity, and iii) which statistical considerations are important. We argue that risk assessment can benefit most from modelling approaches when sensitivity is described based on ecologically relevant and robust effects. Additionally, specific attention should be paid to heterogeneity of the training data (e.g. exposure duration, pH, temperature), since this strongly influences the reliability of the resulting models. Regarding which predictors are useful for explaining differences in species sensitivity, we review interspecies-correlation, relatedness-based, traits-based, and genomic-based extrapolation methods, describing the amount of mechanistic information the predictors contain, the amount of input data the models require, and the extent to which the different methods provide protection for ecological entities. We develop a conceptual framework, incorporating the strengths of each of the methods described. Finally, the discussion of statistical considerations reveals that regardless of the method used, statistically significant models can be found, although the usefulness, applicability, and understanding of these models varies considerably. We therefore recommend publication of scientific code along with scientific studies to simultaneously clarify modelling choices and enable elaboration on existing work. In general, this review specifies the data requirements of different cross-species extrapolation methods, aiming to make regulators and publishers more aware that access to raw- and meta-data needs to be improved to make future cross-species extrapolation efforts successful, enabling their integration into the regulatory environment.

Electronic Health Records and Pulmonary Function Data: Developing an Interoperability Roadmap. An Official American Thoracic Society Workshop Report.

A workshop "Electronic Health Records and Pulmonary Function Data: Developing an Interoperability Roadmap" was held at the American Thoracic Society 2019 International Conference. "Interoperability" is defined as is the ability of different information-technology systems and software applications to directly communicate, exchange data, and use the information that has been exchanged. At present, pulmonary function test (PFT) equipment is not required to be interoperable with other clinical data systems, including electronic health records (EHRs). For this workshop, we assembled a diverse group of experts and stakeholders, including representatives from patient-advocacy groups, adult and pediatric general and pulmonary medicine, informatics, government and healthcare organizations, pulmonary function laboratories, and EHR and PFT equipment and software companies. The participants were tasked with two overarching Aobjectives: 1) identifying the key obstacles to achieving interoperability of PFT systems and the EHR and 2) recommending solutions to the identified obstacles. Successful interoperability of PFT data with the EHR impacts the full scope of individual patient health and clinical care, population health, and research. The existing EHR-PFT device platforms lack sufficient data standardization to promote interoperability. Cost is a major obstacle to PFT-EHR interoperability, and incentives are insufficient to justify the needed investment. The current vendor-EHR system lacks sufficient flexibility, thereby impeding interoperability. To advance the goal of achieving interoperability, next steps include identifying and standardizing priority PFT data elements. To increase the motivation of stakeholders to invest in this effort, it is necessary to demonstrate the benefits of PFT interoperability across patient care and population health.