Predicted distribution of the glass sponge Vazella pourtalesi on the Scotian Shelf and its persistence in the face of climatic variability

Published: 30 May 2019| Version 1 | DOI: 10.17632/zg8k3mchgx.1
Contributors:
Lindsay Beazley,
zeliang wang,
Ellen Kenchington,
Igor Yashayaev,
Hans Tore Rapp,
Joana R. Xavier,
Francisco Murillo,
Derek Fenton,
Susanna Fuller

Description

Emerald Basin on the Scotian Shelf off Nova Scotia, Canada, is home to a globally unique aggregation of the glass sponge Vazella pourtalesi, first documented in the region in 1889. In 2009, Fisheries and Oceans Canada (DFO) implemented two Sponge Conservation Areas to protect these sponge grounds from bottom fishing activities. Together, the two conservation areas encompass 259 km2. In order to ascertain the degree to which the sponge grounds remain unprotected, we modelled the presence probability and predicted range distribution of V. pourtalesi on the Scotian Shelf using random forest modelling on presence-absence records. With a high degree of accuracy the random forest model predicted the highest probability of occurrence of V. pourtalesi in the inner basins on the central Scotian Shelf, with lower probabilities at the shelf break and in the Fundian and Northeast Channels. Bottom temperature was the most important determinant of its distribution in the model. Although the two DFO Sponge Conservation Areas protect some of the more significant concentrations of V. pourtalesi, much of its predicted distribution remains unprotected (over 99%). Examination of the hydrographic conditions in Emerald Basin revealed that the V. pourtalesi sponge grounds are associated with a warmer and more saline water mass compared to the surrounding shelf. Reconstruction of historical bottom temperature and salinity in Emerald Basin revealed strong multi-decadal variability, with average bottom temperatures varying by 8˚C. We show that this species has persisted in the face of this climatic variability, possibly indicating how it will respond to future climate change.

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Institutions

Bedford Institute of Oceanography

Categories

Porifera, Canada, Atlantic Ocean, Probability Distribution, Nova Scotia, Predictive Modeling

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