scholarly journals Incorporating lakes in stream fish habitat models: are we missing a key landscape attribute?

2017 ◽  
Vol 74 (5) ◽  
pp. 629-635 ◽  
Author(s):  
Marc Pépino ◽  
Marco A. Rodríguez ◽  
Pierre Magnan
Keyword(s):  
Relative Abundance ◽  
Brook Trout ◽  
Environmental Variability ◽  
Fish Habitat ◽  
Stream Fish ◽  
Drainage Network ◽  
Stream Networks ◽  
Stream Network ◽  
Habitat Models ◽  
Critical Attribute

Although lakes and rivers are intimately connected, more effort is needed to develop conceptual approaches accounting for lake–stream interactions within the drainage network. Lakes can buffer the impacts of environmental variability in streams and facilitate stream fish recolonization processes. However, lakes have rarely been incorporated in habitat models for stream fish. We examine whether including the presence of lakes in habitat models can improve our understanding of brook trout (Salvelinus fontinalis) abundance in streams. We quantified brook trout relative abundance in 36 streams over 3 consecutive years by single-pass electrofishing. Relative abundance of brook trout in streams was greatest when lakes were present in the stream network. Lakes had greater influence on relative abundance in headwater streams than in larger streams. These results emphasize the importance of considering lakes as a critical attribute in landscape fish habitat models, many of which focus on terrestrial landscape variables. We discuss potential gains from incorporating the presence of lakes in (i) multiscale habitat models, (ii) analyses of spatiotemporal distribution of thermal refuges, and (iii) metrics of habitat connectivity in lake–stream networks.

Are trout populations affected by reach-scale stream slope?

2000 ◽  
Vol 57 (2) ◽  
pp. 468-477 ◽  
Author(s):  
Daniel J Isaak ◽  
Wayne A Hubert
Keyword(s):  
Species Composition ◽  
Spatial Scale ◽  
Relative Abundance ◽  
Cross Sections ◽  
Fish Habitat ◽  
Rocky Mountain ◽  
Mountain Streams ◽  
Habitat Models ◽  
High Slope ◽  
Rocky Mountain Streams

Reach-scale stream slope and the structure of associated physical habitats are thought to affect trout populations, yet previous studies confound the effect of stream slope with other factors that influence trout populations. We isolated the effect of stream slope on trout populations by sampling reaches immediately upstream and downstream of 23 marked changes in stream slope on 18 streams across Wyoming and Idaho. No effect of stream slope on areal trout density was observed, but when trout density was expressed volumetrically to control for differences in channel cross sections among reaches in different slope classes, the highest densities of trout occurred in medium-slope reaches, intermediate densities occurred in high-slope reaches, and the lowest densities occurred in low-slope reaches. The relative abundance of large trout was reciprocal to the pattern in volumetric trout density. Trout biomass and species composition were not affected by stream slope. Our results suggest that an assumption made by many fish-habitat models, that populations are affected by the structure of physical habitats, is at times untenable for trout populations in Rocky Mountain streams and is contingent upon the spatial scale of investigation and the population metric(s) used to describe populations.

Community Ecology of Stream Fishes: Concepts, Approaches, and Techniques

2010 ◽  
Keyword(s):  
Great Plains ◽  
Life Histories ◽  
Environmental Heterogeneity ◽  
Environmental Variability ◽  
Spatial Scales ◽  
Stream Fish ◽  
Metapopulation Dynamics ◽  
Stream Fishes ◽  
Spatial And Temporal Scales ◽  
Trade Offs

<em>Abstract</em>.—Stream fishes carry out their life histories across broad spatial and temporal scales, leading to spatially structured populations. Therefore, incorporating metapopulation dynamics into models of stream fish populations may improve our ability to understand mechanisms regulating them. First, we reviewed empirical research on metapopulation dynamics in the stream fish ecology literature and found 31 papers that used the metapopulation framework. The majority of papers applied no specific metapopulation model, or included space only implicitly. Although parameterization of spatially realistic models is challenging, we suggest that stream fish ecologists should incorporate space into models and recognize that metapopulation types may change across scales. Second, we considered metacommunity theory, which addresses how trade-offs among dispersal, environmental heterogeneity, and biotic interactions structure communities across spatial scales. There are no explicit tests of metacommunity theory using stream fishes to date, so we used data from our research in a Great Plains stream to test the utility of these paradigms. We found that this plains fish metacommunity was structured mainly by spatial factors related to dispersal opportunity and, to a lesser extent, by environmental heterogeneity. Currently, metacommunity models are more heuristic than predictive. Therefore, we propose that future stream fish metacommunity research should focus on developing testable hypotheses that incorporate stream fish life history attributes, and seasonal environmental variability, across spatial scales. This emerging body of research is likely to be valuable not only for basic stream fish ecological research, but also multispecies conservation and management.

scholarly journals Sign Language Recognition Using Two-Stream Convolutional Neural Networks with Wi-Fi Signals

2020 ◽  
Vol 10 (24) ◽  
pp. 9005
Author(s):  
Chien-Cheng Lee ◽  
Zhongjian Gao
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Sign Language ◽  
Recognition Accuracy ◽  
Signal Interference ◽  
Stream Networks ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Stream Network ◽  
Value Decomposition

Sign language is an important way for deaf people to understand and communicate with others. Many researchers use Wi-Fi signals to recognize hand and finger gestures in a non-invasive manner. However, Wi-Fi signals usually contain signal interference, background noise, and mixed multipath noise. In this study, Wi-Fi Channel State Information (CSI) is preprocessed by singular value decomposition (SVD) to obtain the essential signals. Sign language includes the positional relationship of gestures in space and the changes of actions over time. We propose a novel dual-output two-stream convolutional neural network. It not only combines the spatial-stream network and the motion-stream network, but also effectively alleviates the backpropagation problem of the two-stream convolutional neural network (CNN) and improves its recognition accuracy. After the two stream networks are fused, an attention mechanism is applied to select the important features learned by the two-stream networks. Our method has been validated by the public dataset SignFi and adopted five-fold cross-validation. Experimental results show that SVD preprocessing can improve the performance of our dual-output two-stream network. For home, lab, and lab + home environment, the average recognition accuracy rates are 99.13%, 96.79%, and 97.08%, respectively. Compared with other methods, our method has good performance and better generalization capability.

scholarly journals Beaver dam capacity of Canada’s boreal plain in response to environmental change

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nichole-Lynn Stoll ◽  
Cherie J. Westbrook
Keyword(s):  
Environmental Conditions ◽  
Environmental Changes ◽  
Water Cycle ◽  
Stream Networks ◽  
Stream Network ◽  
Beaver Dam ◽  
Riding Mountain National Park ◽  
Induced Changes ◽  
Response To Environmental Change ◽  
Beaver Dams

Abstract Environmental changes are altering the water cycle of Canada’s boreal plain. Beaver dams are well known for increasing water storage and slowing flow through stream networks. For these reasons beavers are increasingly being included in climate change adaptation strategies. But, little work focuses on how environmental changes will affect dam building capacity along stream networks. Here we estimate the capacity of the stream network in Riding Mountain National Park, Manitoba, Canada to support beaver dams under changing environmental conditions using a modelling approach. We show that at capacity, the park’s stream network can support 24,690 beaver dams and hold between 8.2 and 12.8 million m3 of water in beaver ponds. Between 1991 and 2016 the park’s vegetation composition shifted to less preferred beaver forage, which led to a 13% decrease in maximum dam capacity. We also found that dam capacity is sensitive to the size of regularly-occurring floods—doubling the 2-year flood reduces the park’s dam capacity by 21%. The results show that the potential for beaver to offset some expected climatic-induced changes to the boreal water cycle is more complex than previously thought, as there is a feedback wherein dam capacity can be reduced by changing environmental conditions.

Diel variation in stream fish habitat suitability criteria: implications for instream flow assessment

2011 ◽  
Vol 21 (2) ◽  
pp. 132-145 ◽  
Author(s):  
Andrew J. H. Davey ◽  
Douglas J. Booker ◽  
David J. Kelly
Keyword(s):  
Habitat Suitability ◽  
Fish Habitat ◽  
Stream Fish ◽  
Diel Variation ◽  
Instream Flow

Modeling Stream Fish Habitat Limitations from Wedge-Shaped Patterns of Variation in Standing Stock

1996 ◽  
Vol 125 (1) ◽  
pp. 104-117 ◽  
Author(s):  
James W. Terrell ◽  
Brian S. Cade ◽  
Jeanette Carpenter ◽  
Jay M. Thompson
Keyword(s):  
Fish Habitat ◽  
Standing Stock ◽  
Stream Fish

Fyke Net Catches as Indices of the Abundance of Brook Trout, Salvelinus fontinalis, and Atlantic Salmon, Salmo salar

1984 ◽  
Vol 41 (2) ◽  
pp. 377-380 ◽  
Author(s):  
P. M. Ryan
Keyword(s):  
Atlantic Salmon ◽  
Salmo Salar ◽  
Relative Abundance ◽  
Brook Trout ◽  
Salvelinus Fontinalis ◽  
Catch Per Unit Effort ◽  
Small Lakes ◽  
Population Densities ◽  
Atlantic Salmon Salmo Salar ◽  
Fyke Nets

The catch per unit effort (CPUE) data of brook trout (Salvelinus fontinalis) and Atlantic salmon (Salmo salar) in fyke nets set in two small lakes in central Newfoundland were compared with population densities estimated with Schnabel multiple mark–recapture experiments each spring and fall from 1978 to 1982. The catchability of brook trout did not differ significantly between lakes or seasons, and CPUE was an index of the relative abundance of trout within and between lakes. In contrast, the catchability of Atlantic salmon differed greatly between lakes and varied seasonally, being greater in the spring but less in the fall than the catchability of brook trout. Comparisons of relative salmon abundance between lakes or of the relative abundance of brook trout to Atlantic salmon within or between lakes require a correction for seasonal differences in the catchability of salmon.

scholarly journals Drainage Network Analysis and Structuring of Topologically Noisy Vector Stream Data

2019 ◽  
Vol 8 (9) ◽  
pp. 422
Author(s):  
John B. Lindsay ◽  
Wanhong Yang ◽  
Duncan D. Hornby
Keyword(s):  
Network Analysis ◽  
Channel Length ◽  
Drainage Network ◽  
Stream Networks ◽  
Stream Data ◽  
Suitable Alternative ◽  
Analysis Technique ◽  
Digital Elevation ◽  
Topological Errors ◽  
Fine Resolution

Drainage network analysis includes several operations that quantify the topological organization of stream networks. Network analysis operations are frequently performed on streams that are derived from digital elevation models (DEMs). While these methods are suited to application with fine-resolution DEM data, this is not the case for coarse DEMs or low-relief landscapes. In these cases, network analysis that is based on mapped vector streams is an alternative. This study presents a novel vector drainage network analysis technique for performing stream ordering, basin tagging, the identification of main stems and tributaries, and the calculation of total upstream channel length and distance to outlet. The algorithm uses a method for automatically identifying outlet nodes and for determining the upstream-downstream connections among links within vector stream networks while using the priority-flood method. The new algorithm was applied to test stream datasets in two Canadian study areas. The tests demonstrated that the new algorithm could efficiently process large hydrographic layers containing a variety of topological errors. The approach handled topological errors in the hydrography data that have challenged previous methods, including disjoint links, conjoined channels, and heterogeneity in the digitized direction of links. The method can provide a suitable alternative to DEM-based approaches to drainage network analysis, particularly in applications where stream burning would otherwise be necessary.

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