Influence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms

Multiple regression models were used to predict aquaculture production in Pelorus Sound, a 50 km long estuary supporting 68% of New Zealand’s greenshell mussel Perna canaliculus aquaculture industry (worth NZ$204 million per annum). Mussel meat yield was modelled using both biological predictors, in...

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Autores principales:	JR Zeldis, MG Hadfield, DJ Booker
Formato:	article
Lenguaje:	EN
Publicado:	Inter-Research 2013
Materias:	Aquaculture. Fisheries. Angling SH1-691 Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/96f51ee7417b4945a4c023eacfdbd7ef
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spelling	oai:doaj.org-article:96f51ee7417b4945a4c023eacfdbd7ef2021-11-17T10:04:29ZInfluence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms1869-215X1869-753410.3354/aei00066https://doaj.org/article/96f51ee7417b4945a4c023eacfdbd7ef2013-06-01T00:00:00Zhttps://www.int-res.com/abstracts/aei/v4/n1/p1-15/https://doaj.org/toc/1869-215Xhttps://doaj.org/toc/1869-7534Multiple regression models were used to predict aquaculture production in Pelorus Sound, a 50 km long estuary supporting 68% of New Zealand’s greenshell mussel Perna canaliculus aquaculture industry (worth NZ$204 million per annum). Mussel meat yield was modelled using both biological predictors, including seston (indexed by particulate nitrogen, PN), phytoplankton and nutrients collected over 9 yr (July 1997 to November 2005) by the mussel industry, and physical, climatic predictors, including Southern Oscillation Index (SOI), along-shelf winds, sea surface temperature (SST) and Pelorus River flow, held in New Zealand national databases. Yield was best predicted using biological predictors collected locally at the farms inside the sound, but it was also predictable using only physical predictors collected distant from the farming region. Seston (mussel food) was also predictable using the physical predictors. Optimal predictor sets for yield and seston differed between summer and winter half-years. In summer, deep water (which enters the sound through the estuarine circulation) at the sound entrance was nitrate (NO3-)-rich during upwelling conditions (negative SOI, NNW wind stress and cool SST). The increased NO3- levels, in turn, triggered increased PN within the sound. In the winter half-year, PN was unrelated to upwelling and NO3- effects at the entrance and was instead related to river flow. Remotely-sensed SST data showed that in summer, upwelling affected the entrance waters of the sound under negative SOI and upwelling-favourable wind stress, patterns which dissipated in winter. Overall, these results show that time series of physical drivers can be useful for explaining production variation of farmed bivalves and indicate the prospects for using data routinely collected in national databases for predicting mussel yield.JR ZeldisMG HadfieldDJ BookerInter-ResearcharticleAquaculture. Fisheries. AnglingSH1-691EcologyQH540-549.5ENAquaculture Environment Interactions, Vol 4, Iss 1, Pp 1-15 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Aquaculture. Fisheries. Angling SH1-691 Ecology QH540-549.5
spellingShingle	Aquaculture. Fisheries. Angling SH1-691 Ecology QH540-549.5 JR Zeldis MG Hadfield DJ Booker Influence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms
description	Multiple regression models were used to predict aquaculture production in Pelorus Sound, a 50 km long estuary supporting 68% of New Zealand’s greenshell mussel Perna canaliculus aquaculture industry (worth NZ$204 million per annum). Mussel meat yield was modelled using both biological predictors, including seston (indexed by particulate nitrogen, PN), phytoplankton and nutrients collected over 9 yr (July 1997 to November 2005) by the mussel industry, and physical, climatic predictors, including Southern Oscillation Index (SOI), along-shelf winds, sea surface temperature (SST) and Pelorus River flow, held in New Zealand national databases. Yield was best predicted using biological predictors collected locally at the farms inside the sound, but it was also predictable using only physical predictors collected distant from the farming region. Seston (mussel food) was also predictable using the physical predictors. Optimal predictor sets for yield and seston differed between summer and winter half-years. In summer, deep water (which enters the sound through the estuarine circulation) at the sound entrance was nitrate (NO3-)-rich during upwelling conditions (negative SOI, NNW wind stress and cool SST). The increased NO3- levels, in turn, triggered increased PN within the sound. In the winter half-year, PN was unrelated to upwelling and NO3- effects at the entrance and was instead related to river flow. Remotely-sensed SST data showed that in summer, upwelling affected the entrance waters of the sound under negative SOI and upwelling-favourable wind stress, patterns which dissipated in winter. Overall, these results show that time series of physical drivers can be useful for explaining production variation of farmed bivalves and indicate the prospects for using data routinely collected in national databases for predicting mussel yield.
format	article
author	JR Zeldis MG Hadfield DJ Booker
author_facet	JR Zeldis MG Hadfield DJ Booker
author_sort	JR Zeldis
title	Influence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms
title_short	Influence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms
title_full	Influence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms
title_fullStr	Influence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms
title_full_unstemmed	Influence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms
title_sort	influence of climate on pelorus sound mussel aquaculture yields: predictive models and underlying mechanisms
publisher	Inter-Research
publishDate	2013
url	https://doaj.org/article/96f51ee7417b4945a4c023eacfdbd7ef
work_keys_str_mv	AT jrzeldis influenceofclimateonpelorussoundmusselaquacultureyieldspredictivemodelsandunderlyingmechanisms AT mghadfield influenceofclimateonpelorussoundmusselaquacultureyieldspredictivemodelsandunderlyingmechanisms AT djbooker influenceofclimateonpelorussoundmusselaquacultureyieldspredictivemodelsandunderlyingmechanisms
_version_	1718425626729250816

Influence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms

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