A novel method combining species distribution models, remote sensing, and field surveys for detecting and mapping subtidal seagrass meadows

2020 ◽  
Vol 30 (6) ◽  
pp. 1098-1110 ◽  
Author(s):  
Pedro Beca‐Carretero ◽  
Sara Varela ◽  
Dagmar B. Stengel
2018 ◽  
Vol 93 (5) ◽  
pp. 972-977 ◽  
Author(s):  
Joshua L. Sherwood ◽  
Andrew J. Stites ◽  
Michael J. Dreslik ◽  
Jeremy S. Tiemann

2020 ◽  
Vol 239 ◽  
pp. 111626 ◽  
Author(s):  
Christophe F. Randin ◽  
Michael B. Ashcroft ◽  
Janine Bolliger ◽  
Jeannine Cavender-Bares ◽  
Nicholas C. Coops ◽  
...  

2019 ◽  
Vol 28 (11) ◽  
pp. 1578-1596 ◽  
Author(s):  
Jonas J. Lembrechts ◽  
Jonathan Lenoir ◽  
Nina Roth ◽  
Tarek Hattab ◽  
Ann Milbau ◽  
...  

2013 ◽  
Vol 41 (4) ◽  
pp. 736-748 ◽  
Author(s):  
Anna F. Cord ◽  
Doris Klein ◽  
David S. Gernandt ◽  
Jorge A. Pérez de la Rosa ◽  
Stefan Dech

2015 ◽  
Vol 1 (1) ◽  
pp. 4-18 ◽  
Author(s):  
Kate S. He ◽  
Bethany A. Bradley ◽  
Anna F. Cord ◽  
Duccio Rocchini ◽  
Mao‐Ning Tuanmu ◽  
...  

2011 ◽  
Vol 89 (11) ◽  
pp. 1074-1083 ◽  
Author(s):  
D.R. Trumbo ◽  
A.A. Burgett ◽  
J.H. Knouft

Species distribution models (SDMs) have become an important tool for ecologists by providing the ability to predict the distributions of organisms based on species niche parameters and available habitat across broad geographic areas. However, investigation of the appropriate extent of environmental data needed to make accurate predictions has received limited attention. We investigate whether SDMs developed with regional climate and species locality data (i.e., within Missouri, USA) produce more accurate predictions of species occurrences than models developed with data from across an entire species range. To test the accuracy of the model predictions, field surveys were performed in 2007 and 2008 at 103 study ponds for eight amphibian study species. Models developed using data from across the entire species range did not accurately predict the occurrences of any study species. However, models developed using data only from Missouri produced accurate predictions for four study species, all of which are near the edge of their geographic ranges within the study area. These results suggest that species distribution modeling with regionally focused data may be preferable for local ecological and conservation purposes, and that climate factors may be more important for determining species distributions at the edge of their geographic ranges.


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