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Three Rivers, MA, United States

Vezza P.,Polytechnic University of Turin | Parasiewicz P.,Rushing Rivers Institute | Rosso M.,Polytechnic University of Turin | Comoglio C.,Polytechnic University of Turin
River Research and Applications | Year: 2012

In the context of water resources planning, this work defined a possible approach to quantify minimum environmental flows (e-flows) at a regional scale. Focusing on catchments smaller than 50km 2, the problem was addressed through mesoscale habitat models and a catchment classification technique (regression tree algorithm). Within the Piedmont region in NW Italy, 25 reference streams were chosen on the basis of the natural condition of the flow regime and fish community. Mesohabitats were sampled for hydromorphic and fish parameters following the mesoscale habitat models approach. Logistic regression models, along with 55 habitat descriptors, were then used to build multivariate habitat suitability criteria, identifying the habitat characteristics mostly used by the target fish species. These models were applied to each stream reach and used to classify each mesohabitat into suitability categories. The reference minimum discharge for each stream was derived from habitat-flow rating curves. Finally, to define the regional criteria, the study domain was split according to the regression tree classification, defining homogenous sub-regions distinct on both e-flows and catchment/stream characteristics. This bottom-up approach used a catchment classification technique based on the environmental requirements of the fish communities and demonstrated potentials for further applications to defining e-flows at regional scales. © 2011 John Wiley & Sons, Ltd. Source


Azar J.G.,Ecohidraulica S.L. C Rodriguez | Parasiewicz P.,Technical University of Madrid | Alonso-Gonzalez C.,Rushing Rivers Institute | De Jalon D.G.,Ecohidraulica S.L. C Rodriguez
Limnetica | Year: 2011

Physical habitat was assessed in the Tajuña river (Tagus basin, Spain) by means of the MesoHABSIM approach. Long reaches of the Tajuña river are altered by agricultural use of the riverside. The main impacts are river rectification (straightening), channel entrenchment and incision, and degradation of riparian vegetation, along with important flow depletion and regulation. To our knowledge, this is the first application in Spain of MesoHABSIM, which is a physical habitat model based on the identification of habitat attributes - depth, water velocity, substrate, types of hydromorphologic units (HMU), and types of cover - on the mesohabitat scale. The river was stratified into 16 segments with similar habitat characteristics. Mesohabitats were mapped in one representative site (1-2 km long) within each segment to provide a hydromorphologic model of the river. Biological models were developed for fry, juvenile, and adult brown trout. To do this, preliminary models were generated based on literature about trout habitat requirements, and then they were calibrated with electrofishing data. These models were applied to the hydromorphologic model of the river to quantify the available habitat for brown trout in the current conditions. Finally, restoration action was designed to decrease channel entrenchment, increase river sinuosity, and recover its riparian vegetation. The physical changes after restoration were estimated by expert opinion, and the quantification of the available habitat was done with MesoHABSIM at each site. These results can be used to select the segments that are the best candidates for restoration. © Asociación Ibérica de Limnología, Madrid Spain. Source


Vezza P.,Polytechnic University of Turin | Vezza P.,Polytechnic University of Valencia | Parasiewicz P.,Rushing Rivers Institute | Parasiewicz P.,Stanislaw Sakowicz Inland Fisheries Institute | And 2 more authors.
Ecological Applications | Year: 2014

This study aimed to set out a new methodology for habitat modeling in highgradient streams. The methodology is based on the mesoscale approach of the MesoHABSIM simulation system and can support the definition and assessment of environmental flow and habitat restoration measures. Data from 40 study sites located within the mountainous areas of the Valle d'Aosta, Piemonte and Liguria regions (Northwest Italy) were 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 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 was 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 modeling in high-gradient streams, where other commonly used methodologies can be unsuitable. Through its application at several study sites, the proposed methodology adapted well to high-gradient streams and allowed the: (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. © 2014 by the Ecological Society of America. Source


Parasiewicz P.,Rushing Rivers Institute | Parasiewicz P.,Stanislaw Sakowicz Inland Fisheries Institute | Castelli E.,University of Insurbria | Rogers J.N.,Rushing Rivers Institute | Plunkett E.,University of Massachusetts Amherst
Ecological Modelling | Year: 2012

Quantification of the potential habitat available for endangered freshwater mussels can be a challenging task, as habitat use criteria are very complex and often only low numbers of species observations are available. To address this problem in a riverine environment, we developed a concept of a multivariate, multi-scale, and multi-model (multiplex) habitat simulation through combining multivariate time-series analysis of complex hydraulics (CART and logistic regression), micro-scale (River2D), and meso-scale (MesoHABSIM) habitat models, to develop macro-scale management criteria. This concept has been applied and tested on the Upper Delaware River (USA) for the protection and enhancement of existing populations of Alasmidonta heterodon, an endangered freshwater mussel. The physical habitat conditions of approximately 125. km of the Delaware River were described using digital aerial imagery and ground-based surveys. The temporal and spatial variabilities of complex hydraulics simulated by a River2D model at 1547 locations were statistically analyzed to select ranges of attributes that corresponded to mussel presence. We applied these criteria to the river's meso-scale hydromorphological unit mappings to identify suitable mesohabitats, which then served as a calibration data set for the coarser scale model. The final meso-scale model's predictions were hydraulically validated offering encouraging results. The meso-scale habitat suitability criteria defined moderately deep, slow-flowing, and non-turbulent hydromorphologic units as providing good conditions for A. heterodon. All three of the developed suitability models (descriptive statistics, CART and logistic regression model) indicated the species preference for hydraulically stable habitats. © 2012 Elsevier B.V. Source


Vezza P.,Polytechnic University of Valencia | Vezza P.,Polytechnic University of Turin | Parasiewicz P.,Rushing Rivers Institute | Parasiewicz P.,Stanislaw Sakowicz Inland Fisheries Institute | And 4 more authors.
Aquatic Sciences | Year: 2014

In the context of water resources planning and management, the prediction of fish distribution related to habitat characteristics is fundamental for the definition of environmental flows and habitat restoration measures. In particular, threatened and endemic fish species should be the targets of biodiversity safeguard and wildlife conservation actions. The recently developed meso-scale habitat model (MesoHABSIM) can provide solutions in this sense by using multivariate statistical techniques to predict fish species distribution and to define habitat suitability criteria. In this research, Random Forests (RF) and Logistic Regressions (LR) models were used to predict the distribution of bullhead (Cottus gobio) as a function of habitat conditions. In ten reference streams of the Alps (NW Italy), 95 mesohabitats were sampled for hydro-morphologic and biological parameters, and RF and LR were used to distinguish between absence/presence and presence/abundance of fish. The obtained models were compared on the basis of their performances (model accuracy, sensitivity, specificity, Cohen's kappa and area under ROC curve). Results indicate that RF outperformed LR, for both absence/presence (RF: 84 % accuracy, k = 0.58 and AUC = 0.88; LR: 78 % accuracy, k = 0.54 and AUC = 0.85) and presence/abundance models (RF: 79 % accuracy, k = 0.57 and AUC = 0.87; LR: 69 % accuracy, k = 0.43 and AUC = 0.81). The most important variables, selected in each model, are discussed and compared to the available literature. Lastly, results from models' application in regulated sites are presented to show the possible use of RF in predicting habitat availability for fish in Alpine streams. © 2013 Springer Basel. Source

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