scholarly journals Ontogenetic habitat associations of a demersal fish species, Pagrus auratus, identified using boosted regression trees

2012 ◽  
Vol 462 ◽  
pp. 219-230 ◽  
Author(s):  
TJ Compton ◽  
MA Morrison ◽  
JR Leathwick ◽  
GD Carbines
2017 ◽  
Vol 07 (05) ◽  
pp. 859-875 ◽  
Author(s):  
Brigitte Colin ◽  
Samuel Clifford ◽  
Paul Wu ◽  
Samuel Rathmanner ◽  
Kerrie Mengersen

2017 ◽  
Vol 3 (1) ◽  
pp. 55-75 ◽  
Author(s):  
Kate Ingenloff

AbstractBackground: Although pelagic seabirds are broadly recognised as indicators of the health of marine systems, numerous gaps exist in knowledge of their at-sea distributions at the species level. These gaps have profound negative impacts on the robustness of marine conservation policies. Correlative modelling techniques have provided some information, but few studies have explored model development for non-breeding pelagic seabirds. Here, I present a first phase in developing robust niche models for highly mobile species as a baseline for further development. Methodology: Using observational data from a 12-year time period, 217 unique model parameterisations across three correlative modelling algorithms (boosted regression trees, Maxent and minimum volume ellipsoids) were tested in a time-averaged approach for their ability to recreate the at-sea distribution of non-breeding Wandering Albatrosses (Diomedea exulans) to provide a baseline for further development. Principle Findings/Results: Overall, minimum volume ellipsoids outperformed both boosted regression trees and Maxent. However, whilst the latter two algorithms generally overfit the data, minimum volume ellipsoids tended to underfit the data. Conclusions: The results of this exercise suggest a necessary evolution in how correlative modelling for highly mobile species such as pelagic seabirds should be approached. These insights are crucial for understanding seabird-environment interactions at macroscales, which can facilitate the ability to address population declines and inform effective marine conservation policy in the wake of rapid global change.


PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5668 ◽  
Author(s):  
Rachel M. Egly ◽  
Eric R. Larson

Our study evaluates the distribution, habitat associations, and current conservation status of the Snake River pilose crayfish Pacifastacus connectens (Faxon, 1914) and pilose crayfish Pacifastacus gambelii (Girard, 1852), two little-studied and data-deficient species endemic to the western United States. We first developed a species distribution model (SDM) for the pilose crayfishes based on their historical occurrence records using boosted regression trees and freshwater GIS data layers. We then sampled 163 sites in the summers of 2016 and 2017 within the distribution of these crayfishes, including 50 where these species were observed historically. We next compared our field results to modeled predictions of suitable habitat from the SDM. Our SDM predicted 73 sites (45%) we sampled as suitable for the pilose crayfishes, with a moderate AUC value of 0.824. The pilose crayfishes were generally predicted to occur in larger streams and rivers with less extreme upstream temperature and precipitation seasonality. We found the pilose crayfishes at only 20 (12%) of the 163 total sites we sampled, 14 (20%) of the 73 sites predicted as suitable for them by our SDM, and 12 (24%) of 50 historical sites that we sampled. We found the invasive virile crayfish Faxonius virilis (Hagen, 1870) at 22 sites total and 12 (24%) historical sites for the pilose crayfishes, and we found the “native invader” signal crayfish Pacifastacus leniusculus (Dana, 1852) at 29 sites total and 6 (12%) historical sites for the pilose crayfishes. We subsequently used a single classification tree to identify factors associated with our high rate of false positives for contemporary pilose crayfish distributions relative to our SDM. This classification tree identified the presence of invasive crayfishes, impairment of the benthic community, and sampling method as some of the factors differentiating false positives relative to true positives for the pilose crayfishes. Our study identified the historical distribution and habitat associations for P. connectens and P. gambelii using an SDM and contrasted this prediction to results of contemporary field sampling. We found that the pilose crayfishes have seemingly experienced substantial range declines, attributable to apparent displacement by invasive crayfishes and impairment or change to stream communities and habitat. We recommend increased conservation and management attention to P. connectens and P. gambelii in response to these findings.


Author(s):  
Montserrat Demestre ◽  
Pilar Sánchez ◽  
Pere Abelló

Continental shelf and upper slope fish communities were studied along the Catalan coast based on 66 experimental bottom otter trawls. A total of 79 demersal fish species were studied by means of cluster analysis and multi-dimensional scaling (MDS) ordination for community structure. Analysis revealed the existence of five major location clusters. Similarity percentage analysis (SIMPER) was determined by comparing the dissimilarity between two groups of samples using the discriminating species. Geomorphological characteristics, bottom substratum and depth showed direct influences on species assemblages. High correlation between the biotic data samples and depth was observed. The fish species assemblages identified five main demersal fish associations which corresponded with the five location clusters and with five benthic sediments (mud of the upper slope, sand and gravel, mud of the shelf, muddy-sand and sand with rocky outcrops).


2021 ◽  
Author(s):  
Carlotta Valerio ◽  
Graciela Gómez Nicola ◽  
Rocío Aránzazu Baquero Noriega ◽  
Alberto Garrido ◽  
Lucia De Stefano

<p>Since 1970 the number of freshwater species has suffered a decline of 83% worldwide and anthropic activities are considered to be major drivers of ecosystems degradation. Linking the ecological response to the multiple anthropogenic stressors acting in the system is essential to effectively design policy measures to restore riverine ecosystems. However, obtaining quantitative links between stressors and ecological status is still challenging, given the non-linearity of the ecosystem response and the need to consider multiple factors at play. This study applies machine learning techniques to explore the relationships between anthropogenic pressures and the composition of fish communities in the river basins of Castilla-La Mancha, a region covering nearly 79 500 km² in central Spain. During the past two decades, this region has experienced an alarming decline of the conservation status of native fish species. The starting point for the analysis is a 10x10 km grid that defines for each cell the presence or absence of several fish species before and after 2001. This database was used to characterize the evolution of several metrics of fish species richness over time, accounting for the species origin (native or alien), species features (e.g. pollution tolerance) and habitat preferences. Random Forest and Gradient Boosted Regression Trees algorithms were used to relate the resulting metrics to the stressor variables describing the anthropogenic pressures acting in the rivers, such as urban wastewater discharges, land use cover, hydro-morphological degradation and the alteration of the river flow regime. The study provides new, quantitative insights into pressures-ecosystem relationships in rivers and reveals the main factors that lead to the decline of fish richness in Castilla-La Mancha, which could help inform environmental policy initiatives.</p>


Sign in / Sign up

Export Citation Format

Share Document