Random forests to evaluate interspecific interactions in fish distribution models

[EN] Previous research indicated that high predictive performance in species distribution modelling can be obtained by combining both biotic and abiotic habitat variables. However, models developed for fish often only address physical habitat characteristics, thus omitting potentially important biotic factors. Therefore, we assessed the impact of biotic variables on fish habitat preferences in four selected stretches of the upper Cabriel River (E Spain). The occurrence of Squalius pyrenaicus and Luciobarbus guiraonis was related to environmental variables describing biotic interactions (inferred by relationships among fish abundances) and channel hydro-morphological characteristics. Random Forests (RF) models were trained and then validated using independent datasets. To build RF models, the conditional variable importance was used together with the model improvement ratio technique. The procedure showed effectiveness in identifying a parsimonious set of not correlated variables, which minimize noise and improve model performance in both training and validation phases. Water depth, channel width, fine substrate and water-surface gradient were selected as most important habitat variables for both fish. Results showed clear habitat overlapping between fish species and suggest that competition is not a strong factor in the study area.This research has been developed in the framework of the HolRiverMed project (FP7-PEOPLE-2010-275577, Marie Curie Actions, Intra-European Fellowships) and the SCARCE project (Assessing and predicting effects on water quantity and quality in Iberian rivers caused by global change, Consolider-Ingenio 2010 CSD2009-00065). Data collection was partially funded by the Spanish Ministry of Environment, Rural and Marine Affairs, the Jucar River Basin District Authority and the Spanish Ministry of Education and Science (POTECOL, CGL2007-66412). We thank Juan Diego Alacaraz-Hernandez, Matias Peredo-Parada and Aina Hernandez-Mascarell for their help with field work and suggestions on data analysis.Vezza, P.; Muñoz Mas, R.; Martinez-Capel, F.; Mouton, A. (2015). Random forests to evaluate interspecific interactions in fish distribution models. Environmental Modelling and Software. 67:173-183. https://doi.org/10.1016/j.envsoft.2015.01.005S1731836

Physical habitat modelling for fish - a developing approach

Quantitative physical habitat modelling is a river management methodology that has been developed to aid the assessment of the impacts of altered river discharge on freshwater aquatic communities. In this paper we outline the potential value of habitat modelling in advancing the study of fish (particularly 0+ fish) habitat use, and also issues surrounding the inclusion of young fish in environmental impact assessments. Young fish have often been used as target species during such assessments, due to their perceived sensitivity to environmental changes, particularly associated with altered river discharge. However in the past, the paucity of information on young life stages, combined with the general difficulty in quantifying their habitat requirements has limited the use of habitat models for this purpose. Firstly we describe the context within which habitat modelling has been applied traditionally: the development of water resources, and the predictive assessment of associated environmental problems. Alternative approaches to habitat modelling are briefly mentioned. Overall, these techniques, which combine physical and biological data offer a broad perspective for the ecological management of degraded rivers, and can assist in developing our understanding of the processes that influence aquatic organisms in running waters. In the 20 or so years since its inception, habitat modelling has undergone considerable improvement. However there has not been a recent review of such advances. Therefore in the main text, we describe the current state of habitat modelling, emphasising recent developments. Many of these offer possibilities for the advancement of our knowledge of 0+ fish

Manuale tecnico-operativo per la modellazione e la valutazione dell’integrità dell’habitat fluviale

Il presente Manuale descrive la modellazione e la valutazione dell’integrità dell’habitat fluviale utilizzando l’approccio a meso-scala e la metodologia denominata “MesoHABSIM – Mesohabitat Simulation Model”. Tale metodologia, adattata per il contesto italiano, si inserisce nel più ampio “Sistema di Valutazione Idromorfologica, Analsi e Monitoraggio dei corsi d’acqua – IDRAIM” (ISPRA, MLG N° 131/2016). In particolare, la metodologia MesoHABSIM è integrata con il “Sistema di Rilevamento e Classificazione delle Unità Morfologiche dei corsi d’acqua – SUM” (ISPRA, MLG N° 132/2016) per costituire uno strumento atto a descrivere la variabilità spazio-temporale degli habitat fluviali disponibili per la fauna, in funzione della portata defluente e della morfologia del corso d’acqua. La metodologia descritta nel presente manuale è inoltre in accordo con quanto riportato nelle linee guida in tema di “ecological flows” (e-flows) dell’Unione Europea (“Ecological flows in the implementation of the Water Framework Directive”, European Commission, Guidance N° 31, 2015), in cui viene menzionata come strumento idoneo alla valutazione dell’habitat fluviale e utilizzata in due casi studio (casi studio #6 e #8 della guida). Viene infine presentato nel manuale l’Indice di integrità dell’Habitat (IH) e riportati i passi procedurali per la sua applicazione

Habitat modeling in high gradient streams: the meso-scale approach and application

The study aims to set out a new methodology for habitat modeling in high gradient streams. The methodology is based on the meso-scale approach of the MesoHABSIM simulation system and can support the definition and assessment of environmental flow and habitat restoration measures. Data coming from 40 study sites located within the mountainous areas of the Valle d'Aosta, Piemonte and Liguria regions (NW Italy) are used in the analysis. To adapt MesoHABSIM to high gradient streams, we first modified the data collection strategy to address the challenging conditions of surveys by using GIS and mobile mapping techniques. Secondly, we built the habitat suitability models at a regional scale to enable their transferability among different streams with different morphologies. Thirdly, due to the absence of stream gauges in headwaters, we proposed a possible way to simulate flow time series and, therefore, generate habitat time series. The resulting method is evaluated in terms of time expenditure for field data collection and habitat modeling potentials, and it represents a specific improvement of the MesoHABSIM system for habitat modelling in high gradient streams, where other commonly used methodologies can be unsuitable. Through its application in several study sites, the proposed methodology adapts well to high gradient streams and allows: (1) definition of fish habitat requirements for many streams simultaneously, (2) modeling of habitat variation over a range of discharges, and (3) determination of environmental standards for mountainous watercourses