Use of Macroinvertebrate Predictive Models to Evaluate Stream Restoration Effect

Multivariate analysis was used to build macroinvertebrate predictive models for stream assessment in Britain, Australia, and the west coast of the United States. The philosophy behind these predictive models was similar, but variations exist and have been adapted for different regions. The macroinvertebrate predictive model in Maryland has been improved using Region-style models, including the Assessment by Nearest Neighbour Analysis (ANNA), the Burn's Region of Influence (BROI), and the New Datum Region of Influence (NROI) predictive schemes. For better prediction precision, different parameter selection methods (stepwise AIC, exhaustive AIC, and exhaustive BIC) and rational multiple regression function checking have been used to prevent overfitting. Root mean squared error (RMSE) was used to select the final best model. The calibration results from the Region-Style models are better than those from previously built River InVertebrate Prediction And Classification System (RIVPACS)-style model. The different parameter selection criteria along with rational regression function checking discourage overfitting and improve the prediction results. Region-style methods can be alternative methods for building predictive model. GISHydro2000 is a GIS-based program for performing hydrologic analysis in Maryland. This tool was used to determine numerous hydrologic characteristics as potential predictors to be used in the macroinvertebrate predictive model. The best performing ANNA, BROI, and NROI predictive models can be automated in the GISHydro2000 environment. Theses multivariate analyses (i.e., Observed/Expected (O/E) scores), as well as multimetric analysis (i.e., Benthic Index of Biotic Integrity (IBI) metrics), were applied to evaluate the stream restoration sites in Montgomery County, Maryland. The evaluation results show most stream habitat conditions were still degraded after stream restoration projects. The environmental stressors at the stream site were not immediately alleviated by the restoration design, or the stressors overshadowed the restoration efforts. At many sites, the stream condition starts to recover at the 3rd- or 4th- year post-restoration. More time may be needed for monitoring the recovery of stream ecosystems. The benthic IBI metrics response to not only environmental stressor, but also other natural variances. The results suggested that O/E scores from multivariate analysis provides valuable supplemental information for evaluating stream health

Long-term streamflow trends in Hawai'i and implications for native stream fauna

Climate change has fundamentally altered the water cycle in tropical islands, which is a critical driver of freshwater ecosystems. To examine how changes in streamflow regime have impacted habitat quality for native migratory aquatic species, we present a 50‐year (1967–2016) analysis of hydrologic records in 23 unregulated streams across the five largest Hawaiian Islands. For each stream, flow was separated into direct run‐off and baseflow and high‐ and low‐flow statistics (i.e., Q10 and Q90) with ecologically important hydrologic indices (e.g., frequency of flooding and low flow duration) derived. Using Mann–Kendall tests with a running trend analysis, we determined the persistence of streamflow trends through time. We analysed native stream fauna from ~400 sites, sampled from 1992 to 2007, to assess species richness among islands and streams. Declines in streamflow metrics indicated a general drying across the islands. In particular, significant declines in low flow conditions (baseflows), were experienced in 57% of streams, compared with a significant decline in storm flow conditions for 22% of streams. The running trend analysis indicated that many of the significant downward trends were not persistent through time but were only significant if recent decades (1987–2016) were included, with an average decline in baseflow and run‐off of 10.90% and 8.28% per decade, respectively. Streams that supported higher native species diversity were associated with moderate discharge and baseflow index, short duration of low flows, and negligible downward trends in flow. A significant decline in dry season flows (May–October) has led to an increase in the number of no‐flow days in drier areas, indicating that more streams may become intermittent, which has important implications for mauka to makai (mountain to ocean) hydrological connectivity and management of Hawai'i's native migratory freshwater fauna

The Floodwater Depth Estimation Tool (FwDET v2.0) for improved remote sensing analysis of coastal flooding

Remote sensing analysis is routinely used to map flooding extent either retrospectively or in near-real time. For flood emergency response, remote-sensing-based flood mapping is highly valuable as it can offer continued observational information about the flood extent over large geographical domains. Information about the floodwater depth across the inundated domain is important for damage assessment, rescue, and prioritizing of relief resource allocation, but cannot be readily estimated from remote sensing analysis. The Floodwater Depth Estimation Tool (FwDET) was developed to augment remote sensing analysis by calculating water depth based solely on an inundation map with an associated digital elevation model (DEM). The tool was shown to be accurate and was used in flood response activations by the Global Flood Partnership. Here we present a new version of the tool, FwDET v2.0, which enables water depth estimation for coastal flooding. FwDET v2.0 features a new flood boundary identification scheme which accounts for the lack of confinement of coastal flood domains at the shoreline. A new algorithm is used to calculate the local floodwater elevation for each cell, which improves the tool's runtime by a factor of 15 and alleviates inaccurate local boundary assignment across permanent water bodies. FwDET v2.0 is evaluated against physically based hydrodynamic simulations in both riverine and coastal case studies. The results show good correspondence, with an average difference of 0.18 and 0.31&thinsp;m for the coastal (using a 1&thinsp;m DEM) and riverine (using a 10&thinsp;m DEM) case studies, respectively. A FwDET v2.0 application of using remote-sensing-derived flood maps is presented for three case studies. These case studies showcase FwDET v2.0 ability to efficiently provide a synoptic assessment of floodwater. Limitations include challenges in obtaining high-resolution DEMs and increases in uncertainty when applied for highly fragmented flood inundation domains.</p

Characterizing coal and mineral mines as a regional source of stress to stream fish assemblages

Mining impacts on stream systems have historically been studied over small spatial scales, yet investigations over large areas may be useful for characterizing mining as a regional source of stress to stream fishes. The associations between co-occurring stream fish assemblages and densities of various “classes” of mining occurring in the same catchments were tested using threshold analysis. Threshold analysis identifies the point at which fish assemblages change substantially from best available habitat conditions with increasing disturbance. As this occurred over large regions, species comprising fish assemblages were represented by various functional traits as well as other measures of interest to management (characterizing reproductive ecology and life history, habitat preferences, trophic ecology, assemblage diversity and evenness, tolerance to anthropogenic disturbance and state-recognized game species). We used two threshold detection methods: change-point analysis with indicator analysis and piecewise linear regression. We accepted only those thresholds that were highly statistically significant (p ≤ 0.01) for both techniques and overlapped within ≤ 5% error. We found consistent, wedge-shaped declines in multiple fish metrics with increasing levels of mining in catchments, suggesting mines are a regional source of disturbance. Threshold responses were consistent across the three ecoregions occurring at low mine densities. For 47.2% of the significant thresholds, a density of only ≤ 0.01 mines/km² caused a threshold response. In fact, at least 25% of streams in each of our three study ecoregions have mine densities in their catchments with the potential to affect fish assemblages. Compared to other anthropogenic impacts assessed over large areas (agriculture, impervious surface or urban land use), mining had a more pronounced and consistent impact on fish assemblages.Keywords: Game fishes, Rivers, Mining, Threshold analysis, Landscape influences, Fish functional trait

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

ICAR: endoscopic skull‐base surgery

n/

An approach for aggregating upstream catchment information to support research and management of fluvial systems across large landscapes

The growing quality and availability of spatial map layers (e.g., climate, geology, and land use) allow stream studies, which historically have occurred over small areas like a single watershed or stream reach, to increasingly explore questions from a landscape perspective. This large-scale perspective for fluvial studies depends on the ability to characterize influences on streams resulting from throughout entire upstream networks or catchments. While acquiring upstream information for a single reach is relatively straight-forward, this process becomes demanding when attempting to obtain summaries for all streams throughout a stream network and across large basins. Additionally, the complex nature of stream networks, including braided streams, adds to the challenge of accurately generating upstream summaries. This paper outlines an approach to solve these challenges by building a database and applying an algorithm to gather upstream landscape information for digitized stream networks. This approach avoids the need to directly use spatial data files in computation, and efficiently and accurately acquires various types of upstream summaries of landscape information across large regions using tabular processing. In particular, this approach is not limited to the use of any specific database software or programming language, and its flexibility allows it to be adapted to any digitized stream network as long as it meets a few minimum requirements. This efficient approach facilitates the growing demand of acquiring upstream summaries at large geographic scales and helps to support the use of landscape information in assisting management and decision-making across large regions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/2193-1801-3-589) contains supplementary material, which is available to authorized users

Factors associated with prolonged length of stay for elective hepatobiliary and neurosurgery patients: a retrospective medical record review

Abstract Background Patients with prolonged length of hospital stay (LOS) not only increase their risks of nosocomial infections but also deny other patients access to inpatient care. Hepatobiliary (HPB) malignancies have some of highest incidences in East and Southeast Asia and the management of patients undergoing HPB surgeries have yet to be standardized. With improved neurosurgery techniques for intracranial aneurysms and tumors, neurosurgeries (NS) can be expected to increase. Elective surgeries account for far more operations than emergencies surgeries. Thus, with potentially increased numbers of elective HPB and NS, this study seeks to explore perioperative factors associated with prolonged LOS for these patients to improve safety and quality of practice. Methods A retrospective cross-sectional medical record review study from January 2014 to January 2015 was conducted at a 1250-bed tertiary academic hospital in Singapore. All elective HPB and NS patients over 18 years old were included in the study except day and emergency surgeries, resulting in 150 and 166 patients respectively. Prolonged LOS was defined as above median LOS based on the complexity of the surgical procedure. The predictor variables were preoperative, intraoperative, and postoperative factors. Student’s t-test and stepwise logistic regression analyses were conducted to determine which factors were associated with prolonged LOS. Results Factors associated with prolonged LOS for the HPB sample were age and admission after 5 pm but for the NS sample, they were functional status, referral to occupational therapy, and the number of hospital-acquired infections. Conclusion Our findings indicate that preoperative factors had the greatest association with prolonged LOS for HPB and NS elective surgeries even after adjusting for surgical complexity, suggesting that patient safety and quality of care may be improved with better pre-surgery patient preparation and admission practices