Limited transferability of stream-fish distribution models among river catchments: reasons and implications

2016 ◽  
Vol 61 (5) ◽  
pp. 729-744 ◽  
Author(s):  
Jian Huang ◽  
Emmanuel A. Frimpong
Keyword(s):  
Fish Distribution ◽  
Stream Fish ◽  
Distribution Models ◽  
River Catchments

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

2010 ◽  
Keyword(s):  
Climate Change ◽  
Fish Species ◽  
Species Distribution ◽  
General Circulation ◽  
Greenhouse Gas Emission ◽  
General Circulation Models ◽  
Consensus Method ◽  
Stream Fish ◽  
Emission Scenarios ◽  
Distribution Models

<em>Abstract</em>.—Stream fish are expected to be influenced by climate change as they are ectothermic animals living in lotic systems. Using fish presence–absence records in 1,110 stream sites across France, our study aimed at (1) modeling current and future distributions of 35 stream fish species, (2) using an ensemble forecasting approach (i.e., several general circulation models [GCM] × greenhouse gas emission scenarios [GES] × statistical species distribution models [SDM] combinations) to quantify the variability in the future fish species distribution due to each component, and (3) assessing the potential impacts of climate change on fish species distribution and assemblage structure by using a consensus method that accounted for the variability in future projections.

Distribution, abundance, and diversity of stream fishes under variable environmental conditions

2006 ◽  
Vol 63 (1) ◽  
pp. 43-54 ◽  
Author(s):  
Christopher M Taylor ◽  
Thomas L Holder ◽  
Riccardo A Fiorillo ◽  
Lance R Williams ◽  
R Brent Thomas ◽  
...  
Keyword(s):  
Species Richness ◽  
Environmental Conditions ◽  
Community Dynamics ◽  
Local Community ◽  
Fish Assemblages ◽  
Fish Distribution ◽  
Stream Fish ◽  
Spatial And Temporal Variability ◽  
Regional Patterns ◽  
Abundance And Diversity

The effects of stream size and flow regime on spatial and temporal variability of stream fish distribution, abundance, and diversity patterns were investigated. Assemblage variability and species richness were each significantly associated with a complex environmental gradient contrasting smaller, hydrologically variable stream localities with larger localities characterized by more stable flow regimes. Assemblages showing the least variability were the most species-rich and occurred in relatively large, stable environments. Theory suggests that species richness can be an important determinant of assemblage variability. Although this appears to be true in our system, we suggest that spatial and temporal heterogeneity in the environment largely determines both assemblage richness and variability, providing a more parsimonious explanation for the diversity–variability correlation. Changes in species richness of local assemblages across time were coordinated across the landscape, and assemblages formed spatially and temporally nested subset patterns. These results suggest an important link between local community dynamics and community-wide occurrence. At the species level, mean local persistence was significantly associated with regional occurrence. Thus, the more widespread a species was, the greater its local persistence. Our results illustrate how the integrity of local stream fish assemblages is dependent on local environmental conditions, regional patterns of species distribution, and landscape continuity.

scholarly journals The use of singlebeam echo‐sounder depth data to produce demersal fish distribution models that are comparable to models produced using multibeam echo‐sounder depth

2021 ◽  
Author(s):  
Marcela Montserrat Landero Figueroa ◽  
Miles J. G. Parsons ◽  
Benjamin J. Saunders ◽  
Ben Radford ◽  
Chandra Salgado‐Kent ◽  
...  
Keyword(s):  
Demersal Fish ◽  
Fish Distribution ◽  
Distribution Models ◽  
Depth Data ◽  
Echo Sounder

scholarly journals Accounting for detectability in fish distribution models: an approach based on time-to-first-detection

2015 ◽  
Vol 2 ◽  
Author(s):  
Ferreira Mário ◽  
Filipe Ana Filipa ◽  
Magalhães Filomena ◽  
Beja Pedro
Keyword(s):  
Fish Distribution ◽  
Distribution Models

scholarly journals Random forests to evaluate biotic interactions in fish distribution models

2015 ◽  
Vol 67 ◽  
pp. 173-183 ◽  
Author(s):  
P. Vezza ◽  
R. Muñoz-Mas ◽  
F. Martinez-Capel ◽  
A. Mouton
Keyword(s):  
Random Forests ◽  
Biotic Interactions ◽  
Fish Distribution ◽  
Distribution Models

The iterative ensemble modelling approach increases the accuracy of fish distribution models

Ecography ◽  
2014 ◽  
Vol 38 (2) ◽  
pp. 213-220 ◽  
Author(s):  
Christine Lauzeral ◽  
Gaël Grenouillet ◽  
Sébastien Brosse
Keyword(s):  
Fish Distribution ◽  
Distribution Models ◽  
Ensemble Modelling ◽  
Modelling Approach

scholarly journals Testing the Improvement of Coral Reef Associated Fish Distribution Models Based on Multibeam Bathymetry by Adding Seafloor Backscatter Data

2021 ◽  
Vol 8 ◽  
Author(s):  
Marcela Montserrat Landero Figueroa ◽  
Miles J. G. Parsons ◽  
Benjamin J. Saunders ◽  
Ben Radford ◽  
Iain M. Parnum
Keyword(s):  
Strong Relationship ◽  
Demersal Fish ◽  
Important Variable ◽  
Acoustic Energy ◽  
Fish Distribution ◽  
Distribution Models ◽  
Seafloor Morphology ◽  
Seafloor Backscatter ◽  
Using Data ◽  
Lagocephalus Sceleratus

Demersal fishes constitute an essential component of the continental shelf ecosystem, and a significant element of fisheries catch around the world. However, collecting distribution and abundance data of demersal fish, necessary for their conservation and management, is usually expensive and logistically complex. The increasing availability of seafloor mapping technologies has led to the opportunity to exploit the strong relationship demersal fish exhibit with seafloor morphology to model their distribution. Multibeam echo-sounder (MBES) systems are a standard method to map seafloor morphology. The amount of acoustic energy reflected by the seafloor (backscatter) is used to estimate specific characteristics of the seafloor, including acoustic hardness and roughness. MBES data including bathymetry and depth derivatives were used to model the distribution of Abalistes stellatus, Gymnocranius grandoculis, Lagocephalus sceleratus, Lethrinus miniatus, Loxodon macrorhinus, Lutjanus sebae, and Scomberomorus queenslandicus. The possible improvement of model accuracy by adding the seafloor backscatter was tested in three different areas of the Ningaloo Marine Park off the west coast of Australia. For the majority of species, depth was a primary variable explaining their distribution in the three study sites. Backscatter was identified to be an important variable in the models, but did not necessarily lead to a significant improvement in the demersal fish distribution models’ accuracy. Possible reasons for this include: the depth and derivatives were capturing the significant changes in the habitat, or the acoustic data collected with a high-frequency MBES were not capturing accurately relevant seafloor characteristics associated with the species distribution. The improvement in the accuracy of the models for certain species using data already available is an encouraging result, which can have a direct impact in our ability to monitor these species.

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