Uncertainty in Various Habitat Suitability Models and Its Impact on Habitat Suitability Estimates for Fish

Developing a statistical-weighted index of biotic integrity for large-river ecological evaluations

The efficiency, accuracy and universality of ecological assessment methods comprise an important foundation for comprehensive assessment and restoration of large river ecological health at the watershed scale. New evaluation metrics and methods are urgently needed to be developed to adapt the characteristics of large rivers, including geographical differences in surface runoff, regional ecological complexity, and seasonal changes. In this study, a bacteria-weighted index of biotic integrity was developed to assess the ecological health of large rivers (lrBW-IBI) based on compositional and functional characteristics of sediment bacterial communities from 33 sections of the lower mainstream of Yangtze River. Five key metrics were determined by range, responsiveness, and redundancy tests. Principal component analysis (PCA), entropy method, criteria importance through intercriteria correlation and random forest were applied to calculate weighted coefficients of key metrics. The optimal lrBW-IBI was observed through the sum of PCA weighted-metrics: the relative abundance of Latescibacteria (0.234), Gemmatimonadaceae (0.149), Nitrospira spp. (0.234), Rhizobiales (0.228), and nitrogenase NifH (0.156). According to PCA based lrBW-IBI, 12.12%, 24.24%, 39.39%, and 24.24% of river sections were labeled excellent, good, moderate, and relatively poor, respectively. The ecological status of the lower mainstream of the Yangtze River did not change significantly across seasons but declined gradually from upstream to downstream. This study provides a new assessment tool for the ecological health of large rivers and highlights the importance of microbial ecological index in river ecology.

A Brief Review of Random Forests for Water Scientists and Practitioners and Their Recent History in Water Resources

Random forests (RF) is a supervised machine learning algorithm, which has recently started to gain prominence in water resources applications. However, existing applications are generally restricted to the implementation of Breiman’s original algorithm for regression and classification problems, while numerous developments could be also useful in solving diverse practical problems in the water sector. Here we popularize RF and their variants for the practicing water scientist, and discuss related concepts and techniques, which have received less attention from the water science and hydrologic communities. In doing so, we review RF applications in water resources, highlight the potential of the original algorithm and its variants, and assess the degree of RF exploitation in a diverse range of applications. Relevant implementations of random forests, as well as related concepts and techniques in the R programming language, are also covered.

Physical habitat simulation for small-sized characid fish species from tropical rivers in Brazil

ABSTRACT Physical habitat simulation (PHABSIM) is an important step of the instream flow incremental methodology (IFIM), which is applied to establish environmental flow regimes. This study applied the PHABSIM in two reaches of the Velhas river basin, whose long-term discharges are similar but are under different degrees of impact. Suitability curves were obtained for fish species using traditional methods (Astyanax sp., Piabarchus stramineus, Piabina argentea and Serrapinnus heterodon) and generalized additive models for fish density (Astyanax sp., P. argentea and S. heterodon). The results of habitat use depended on the method for curves generation. Applying the suitability curves by traditional methods, different discharge scenarios were simulated. The flow increasing from a dry scenario to a discharge of 1 year of return promotes a possible habitat increase for all species. However, the same hydrological flow percentiles produce different habitat proportions in different rivers. This work demonstrates that regardless of how suitability curves for the Neotropical species are generated, caution should be taken when applying them. However, the PHABSIM method allows more complex analyses than the traditional approaches based on minimal flow estimations, which is usually applied in South America.

Development of an Evaluation System for Sustaining Reservoir Functions—A Case Study of Shiwen Reservoir in Taiwan

Reservoirs serve as important facilities, providing a stable source of public water in Taiwan. As construction of new reservoirs becomes more difficult, it is essential to ensure sustainable functionality of reservoirs in the future. To this end, this study proposes a system for reservoir sustainability evaluation. The evaluation system consists of social justice, environmental protection, and economic development containing 12 indicators which are grouped into six categories: flood control, sediment management, water resources allocation, river ecology, water quality, and benefit and fairness. Moreover, evaluation system operational procedures to supplement planning and decision-making processes are proposed, and applied in a case study of the Shiwen reservoir planning in Taiwan. The planned reservoir in this case study is rated as “Good”, nearly “Excellent”, in sustainability as evaluated with the Sustainability Confidence Index (SCI). Additionally, Analytic Network Process (ANP) results indicate that the flood control capacity and sediment management are the first and second most important indicators for the reservoir. If desilting operations had been conducted, the SCI values would have increased from 3.3 to 3.7, warranting an “Excellent” rating for the reservoir. The case study demonstrates that decision-makers can apply the proposed system when managing reservoir evaluations.

Shifts in the suitable habitat available for brown trout (Salmo trutta L.) under short-term climate change scenarios

The impact of climate change on the habitat suitability for large brown trout (Salmo trutta L.) was studied in a segment of the Cabriel River (Iberian Peninsula). The future flow and water temperature patterns were simulated at a daily time step with M5 models' trees (NSE of 0.78 and 0.97 respectively) for two short-term scenarios (2011-2040) under the representative concentration pathways (RCP 4.5 and 8.5). An ensemble of five strongly regularized machine learning techniques (generalized additive models, multilayer perceptron ensembles, random forests, support vector machines and fuzzy rule base systems) was used to model the microhabitat suitability (depth, velocity and substrate) during summertime and to evaluate several flows simulated with River2D©. The simulated flow rate and water temperature were combined with the microhabitat assessment to infer bivariate habitat duration curves (BHDCs) under historical conditions and climate change scenarios using either the weighted usable area (WUA) or the Boolean-based suitable area (SA). The forecasts for both scenarios jointly predicted a significant reduction in the flow rate and an increase in water temperature (mean rate of change of ca. -25% and +4% respectively). The five techniques converged on the modelled suitability and habitat preferences; large brown trout selected relatively high flow velocity, large depth and coarse substrate. However, the model developed with support vector machines presented a significantly trimmed output range (max.: 0.38), and thus its predictions were banned from the WUA-based analyses. The BHDCs based on the WUA and the SA broadly matched, indicating an increase in the number of days with less suitable habitat available (WUA and SA) and/or with higher water temperature (trout will endure impoverished environmental conditions ca. 82% of the days). Finally, our results suggested the potential extirpation of the species from the study site during short time spans.