Marine species distribution shifts on the U.S. Northeast Continental Shelf under continued ocean warming

2017 ◽  
Vol 153 ◽  
pp. 24-36 ◽  
Author(s):  
Kristin M. Kleisner ◽  
Michael J. Fogarty ◽  
Sally McGee ◽  
Jonathan A. Hare ◽  
Skye Moret ◽  
...  
Author(s):  
Christopher N Rooper ◽  
Ivonne Ortiz ◽  
Albert J Hermann ◽  
Ned Laman ◽  
Wei Cheng ◽  
...  

Abstract Climate-related distribution shifts for marine species are, in general, amplified in northern latitudes. The objective of this study was to predict future distributions of commercially important species in the eastern Bering Sea under six climate scenarios, by incorporating predictions of future oceanographic conditions. We used species distribution modelling to determine potential distribution changes in four time periods (2013–2017, 2030–2039, 2060–2069, and 2090-2099) relative to 1982–2012 for 16 marine fish and invertebrates. Most species were predicted to have significant shifts in the centre of gravity of the predicted abundance, the area occupied, and the proportion of the predicted abundance found in the standard bottom trawl survey area. On average the shifts were modest, averaging 35.2 km (ranging from 1 to 202 km). There were significant differences in the predicted trend for distribution metrics among climate scenarios, with the most extensive changes in distribution resulting from Representative Concentration Pathway 8.5 climate scenarios. The variability in distributional shifts among years and climate scenarios was high, although the magnitudes were low. This study provides a basis for understanding where fish populations might expand or contract in future years. This will provide managers’ information that can help guide appropriate actions under warming conditions.


2018 ◽  
Vol 80 (6) ◽  
pp. 457-461
Author(s):  
Carlos A. Morales-Ramirez ◽  
Pearlyn Y. Pang

Open-source data are information provided free online. It is gaining popularity in science research, especially for modeling species distribution. MaxEnt is an open-source software that models using presence-only data and environmental variables. These variables can also be found online and are generally free. Using all of these open-source data and tools makes species distribution modeling (SDM) more accessible. With the rapid changes our planet is undergoing, SDM helps understand future habitat suitability for species. Due to increasing interest in biogeographic research, SDM has increased for marine species, which were previously not commonly found in this modeling. Here we provide examples of where to obtain the data and how the modeling can be performed and taught.


2004 ◽  
Vol 26 (2) ◽  
pp. 239-259 ◽  
Author(s):  
Omowumi O. Iledare ◽  
Allan G. Pulsipher ◽  
Williams O. Olatubi ◽  
Dmitry V. Mesyanzhinov

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