Defining a procedure for integrating multiple oceanographic variables in ensemble models of marine species distribution

Author(s):  
Diego Panzeri ◽  
Simone Libralato ◽  
Roberto Carlucci ◽  
Giulia Cipriano ◽  
Isabella Bitetto ◽  
...  
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.


2016 ◽  
Vol 22 (7) ◽  
pp. 808-822 ◽  
Author(s):  
David A. Stirling ◽  
Philip Boulcott ◽  
Beth E. Scott ◽  
Peter J. Wright

2014 ◽  
Vol 23 (12) ◽  
pp. 1417-1429 ◽  
Author(s):  
Tarek Hattab ◽  
Camille Albouy ◽  
Frida Ben Rais Lasram ◽  
Samuel Somot ◽  
François Le Loc'h ◽  
...  

Author(s):  
Cemal Turan

The progress on species distribution modelling (SDM) methods has brought new insights into the field of biological invasion management. In particular, statistical niche modelling, for spatio-temporal predictions of marine species’ distribution, is an increasingly used tool, supporting efficient decision-making for prevention and conservation. Earth's climate has changed significantly in the last century and the number of alien species penetrating from Indo-Pacific Ocean and South part of the Atlantic in the Mediterranean will continue to increase over the next decades. The purpose of the present study was to predict the potential geographic distribution and expansion of invasive alien lionfish (Pterois miles and Pterois volitans) with ecological niche modelling along the Mediterranean Sea. Temporal and spatial occurrence data from the first occurrence of a species for each country with coast along the Mediterranean Sea, was used to develop robust predictions of species richness, since the capacity to predict spatial patterns of species richness remains largely unassessed in this region. Marine climatic data layers were collected from the Bio-ORACLE and MARSPEC global databases. Different statistical models were evaluated to establish if these could provide useful predictions of absolute and relative lionfish distribution and expansion. The findings are an important step towards validating the use of SDM for invasive alien lionfish in the Mediterranean Sea.


2015 ◽  
Vol 3 ◽  
pp. e4900 ◽  
Author(s):  
John Wood ◽  
Fabio Moretzsohn ◽  
James Gibeaut

2018 ◽  
Vol 8 (24) ◽  
pp. 12867-12878
Author(s):  
Claire M. Curry ◽  
Jeremy D. Ross ◽  
Andrea J. Contina ◽  
Eli S. Bridge

2017 ◽  
Vol 153 ◽  
pp. 24-36 ◽  
Author(s):  
Kristin M. Kleisner ◽  
Michael J. Fogarty ◽  
Sally McGee ◽  
Jonathan A. Hare ◽  
Skye Moret ◽  
...  

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