Multi-objective optimisation of species distribution models for river management

Multiobjective optimization algorithm for accurate MADYMO reconstruction of vehicle-pedestrian accidents

In vehicle-pedestrian accidents, the preimpact conditions of pedestrians and vehicles are frequently uncertain. The incident data for a crash, such as vehicle deformation, injury of the victim, distance of initial position and rest position of accident participants, are useful for verification in MAthematical DYnamic MOdels (MADYMO) simulations. The purpose of this study is to explore the use of an improved optimization algorithm combined with MADYMO multibody simulations and crash data to conduct accurate reconstructions of vehicle-pedestrian accidents. The objective function of the optimization problem was defined as the Euclidean distance between the known vehicle, human and ground contact points, and multiobjective optimization algorithms were employed to obtain the local minima of the objective function. Three common multiobjective optimization algorithms-nondominated sorting genetic algorithm-II (NSGA-II), neighbourhood cultivation genetic algorithm (NCGA), and multiobjective particle swarm optimization (MOPSO)-were compared. The effect of the number of objective functions, the choice of different objective functions and the optimal number of iterations were also considered. The final reconstructed results were compared with the process of a real accident. Based on the results of the reconstruction of a real-world accident, the present study indicated that NSGA-II had better convergence and generated more noninferior solutions and better final solutions than NCGA and MOPSO. In addition, when all vehicle-pedestrian-ground contacts were considered, the results showed a better match in terms of kinematic response. NSGA-II converged within 100 generations. This study indicated that multibody simulations coupled with optimization algorithms can be used to accurately reconstruct vehicle-pedestrian collisions.

Predicting catchment suitability for biodiversity at national scales

Biomonitoring of water quality and catchment management are often disconnected, due to mismatching scales. Considerable effort and money are spent each year on routine reach-scale surveying across many sites, particularly in countries like the UK, where nationwide sampling has been conducted using standardised techniques for many decades. Most of these traditional freshwater biomonitoring schemes focus on pre-defined indicators of organic pollution to compare observed vs expected subsets of common macroinvertebrate indicator species. Other taxa, including many threatened species, are often ignored due to their rarity, as are many invasive species, which are seen as undesirable despite becoming increasingly common and widespread in freshwaters, especially in urban ecosystems. Both these types of taxa are often monitored separately for reasons related to biodiversity concerns rather than for gauging water quality. Repurposing such data could therefore provide important new biomonitoring tools that can help catchment managers to directly link the water quality they aim to control with the biodiversity they are trying to protect. Here we used extensive data held in the England Non-Native and Rare/Protected species records that track these two groups of species as a proof-of-concept for linking catchment scale management of freshwater ecosystems and biodiversity to a range of potential drivers across England. We used national land use (Centre for Ecology and Hydrology land cover map) and water quality indicator (Environment Agency water quality data archive) datasets to predict, at the catchment scale, the presence or absence of 48 focal threatened or invasive species of concern routinely sampled by the English Environment Agency, with a median accuracy of 0.81 area under the receiver operating characteristic curve. A variety of water quality indicators and land-use types were useful in predictions, highlighting that future biomonitoring schemes could use such complementary measures to capture a wider spectrum of drivers and responses. In particular, the percentage of a catchment covered by freshwater was the single most important metric, reinforcing the need for space/habitat to support biodiversity, but we were also able to resolve a range of key environmental drivers for particular focal species. We show how our method could inform new catchment management approaches, by highlighting how key relationships can be identified and how to understand, visualise and prioritise catchments that are most suitable for restoration or water quality interventions. The scale of this work, in terms of number of species, drivers and locations, represents a significant step towards forging a new approach to catchment management that enables managers to link drivers they can control (water quality and land use) to the biota they are trying to protect (biodiversity).

Capturing response differences of species distribution to climate and human pressures by incorporating local adaptation: Implications for the conservation of a critically endangered species

Considering local adaptation has been increasingly involved in forecasting species distributions under climate change and the management of species conservation. Herein, we take the critically endangered Chinese giant salamander (Andrias davidianus) that has both a low dispersal ability and distinct population divergence in different regions as an example. Basin-scale models that represent different populations in the Huanghe River Basin (HRB), the Yangtze River Basin (YRB), and the Pearl River Basin (PRB) were established using ensemble species distribution models. The species ranges under the future human population density (HPD) and climate change were predicted, and the range loss was evaluated for local basins in 2050 and 2070. Our results showed that the predominant factors affecting species distributions differed among basins, and the responses of the species occurrence to HPD and climate factors were distinctly different from northern to southern basins. Future HPD changes would be the most influential factor that engenders negative impacts on the species distribution in all three basins, especially in the HRB. Climate change will likely be less prominent in decreasing the species range, excluding in the YRB and PRB under the highest-emissions scenario in 2050. Overall, the high-emissions scenario would more significantly aggravate the negative impacts produced by HPD change in both 2050 and 2070, with maximum losses of species ranges in the HRB, YRB, and PRB of 83.4%, 60.0%, and 53.5%, respectively, under the scenarios of the combined impacts of HPD and climate changes. We proposed adapted conservation policies to effectively protect the habitat of this critically endangered animal in different basins based on the outcomes. Our research addresses the importance of incorporating local adaptation into species distribution modeling to inform conservation and management decisions.

A framework for determining the maximum allowable external load that will meet a guarantee probability of achieving water quality targets

Quantifying the maximum external pollutant loading is extremely important for environmental management and ecological restoration. However, huge uncertainty exists in the process of determining accurate external pollutant loads discharging into surface water bodies (e.g., rivers, reservoirs, and bays). In this paper, a comprehensive framework is proposed for determining the maximum allowable external load by combining a dynamic nutrient-balance model with the guarantee probability of achieving a specific water quality target. As an important drinking water source for Beijing, the Miyun Reservoir was chosen as a case study because it is experiencing increasing eutrophication. The main results are as follows. ① The nutrient-balance model has shown a good fit to field observations both in calibration and validation periods using the modified Generalized Likelihood Uncertainty Estimation (GLUE). ② Feasible concentration targets were determined for total phosphorus (TP), total nitrogen (TN), and chlorophyll-a as 0.01 mg/L, 0.76 mg/L, and 4.91 μg/L, respectively. ③ The allowable external load of TP is estimated as 45.10-54.14 t, 23.76-29.58 t, and 8.30-12.78 t for guarantee probabilities of TP control target (e.g., 0.01 mg/L) of 25, 50, and 70%, respectively. While the external TN flux should be reduced by 200.21-480.73 t, 429.33-764.45 t, and 642.40-1069.59 t to meet the TN control target (e.g., 0.76 mg/L) at 25, 50, and 70% guarantee probabilities, respectively, The wide range of allowable external nutrient loading reflects the 95% confidence intervals of the load reduction analysis and indicates the importance of model simulation uncertainty and interpretation of the water quality objective. This paper provides a scientifically sound approach to water quality maintenance for the Miyun Reservoir and other surface water bodies.