The replacement of a native freshwater amphipod by an invader: roles for environmental degradation and intraguild predation

We assessed the extent to which an invader, Gammarus pulex (Crustacea: Amphipoda), has replaced a native, Gammarus duebeni celticus, over a 13-year period in a European river system and some of the abiotic and biotic factors that could account for this. Between 1988 and 2001, 56% of mixed-species sites had become invader-only sites, whereas no mixed sites had become native only again. The native dominated areas of higher dissolved oxygen and water quality, with the reciprocal true for the invader. Field transplant experiments revealed that native survivorship was lower in areas where it had been replaced than in areas where the invader does not yet occur. In invader-only areas, native survivorship was lower than that of the invader when kept separately and lowest when both species were kept together. We also observed predation of the native by the invader. Laboratory oxygen manipulation experiments revealed that at 30% saturation, the native's survivorship was two thirds that of the invader. We conclude that decreasing water quality favours replacement of the native by the invader.9 page(s

International regulatory responses to global challenges in marine pollution and climate change

Marine pollution, also referred to as \u27pollution of the marine environment\u27, may occur as a result of different activities. Examples are land-based activities, vessel-related activitiese, dumping at sea, atmospheric and offshore hydrocarbon exploration, seabed mining, and so on. As discussed in Chapter 4, these types of marine pollution are often transboundary in nature and are harmful to human health and marine ecosystem. Similarly, climate change is a global issue involving the interests of all States. The Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), finalized and published in 2014, has further confirmed the existence of global warming when compared with the previous IPCC reports. It indicates that climate change has negatively affected natural and human systems on all continents and across the oceans, and asserts that 280substantial and sustained reduction of greenhouse gas (GHG) emissions would contribute to the tackling of climate change. 1 International issues need international responses. Both the marine pollution and climate change are issues with international dimensions, and thus require the global regulation by the international community

A Machine Learning Algorithm to Identify Patients at Risk of Unplanned Subsequent Surgery After Intramedullary Nailing for Tibial Shaft Fractures

Objectives: In the SPRINT trial, 18% of patients with a tibial shaft fracture (TSF) treated with intramedullary nailing (IMN) had one or more unplanned subsequent surgical procedures. It is clinically relevant for surgeon and patient to anticipate unplanned secondary procedures, other than operations that can be readily expected such as reconstructive procedures for soft tissue defects. Therefore, the objective of this study was to develop a machine learning (ML) prediction model using the SPRINT data that can give individual patients and their care team an estimate of their particular probability of an unplanned second surgery. Methods: Patients from the SPRINT trial with unilateral TSFs were randomly divided into a training set (80%) and test set (20%). Five ML algorithms were trained in recognizing patterns associated with subsequent surgery in the training set based on a subset of variables identified by random forest algorithms. Performance of each ML algorithm was evaluated and compared based on (1) area under the ROC curve, (2) calibration slope and intercept, and (3) the Brier score. Results: Total data set comprised 1198 patients, of whom 214 patients (18%) underwent subsequent surgery. Seven variables were used to train ML algorithms: (1) Gustilo-Anderson classification, (2) Tscherne classification, (3) fracture location, (4) fracture gap, (5) polytrauma, (6) injury mechanism, and (7) OTA/AO classification. The best-performing ML algorithm had an area under the ROC curve, calibration slope, calibration intercept, and the Brier score of 0.766, 0.954, -0.002, and 0.120 in the training set and 0.773, 0.922, 0, and 0.119 in the test set, respectively. Conclusions: An ML algorithm was developed to predict the probability of subsequent surgery after IMN for TSFs. This ML algorithm may assist surgeons to inform patients about the probability of subsequent surgery and might help to identify patients who need a different perioperative plan or a more intensive approach.Orthopaedics, Trauma Surgery and Rehabilitatio