Seagrass valuation from fish abundance, biomass and recreational catch

Holger Jänes,Paul Carnell,Mary Young,Daniel Ierodiaconou,Gregory P Jenkins,Paul Hamer,Philine S.E Zu Ermgassen,Jonathan R Gair,Peter I Macreadie

doi:10.1016/j.ecolind.2021.108097

Holger Jänes, Paul Carnell + Show 7 more

Open Access

https://doi.org/10.1016/j.ecolind.2021.108097

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Abstract

The value of critical habitats, such as seagrass, to act as a nursery varies spatially and temporally; however, such information is essential for the public and stakeholders to appropriately value and manage these habitats. We use an existing systematic long-term fisheries dataset in Port Phillip Bay to examine variability in nursery habitat value for an important commercial and recreational species, King George Whiting (Sillaginodes punctatus). Port Phillip Bay represents one of the most important marine assets in the southern hemisphere and is surrounded by the second-largest city in Australia, Melbourne, home to 4.5 million people. We modelled the abundance of King George whiting as a function of environmental variables, using Boosted Regression Trees (BRT). Fish densities ranged from 1,000 to 30,000 individuals ha−1y−1, equalling an adult biomass of 110–3,300 kg ha−1y−1. This production supports between 69 and 2,062 recreational fishing trips a year, with an estimated value of seagrass of AUD 687–20,625 ha−1y−1. Based on biomass production of King George Whiting and recreational fisheries data, the 6662 ha of seagrass in Port Phillip Bay are valued at around AUD 36 million annually.

Highlights

Marine fisheries play a key role in global food security, supporting coastal communities’ socio-economic well-being through recreational and commercial fishing and associated industries
Juvenile fish abundances from individual sampling locations were combined with environmental variables and analysed with Boosted Regression Trees (BRT) modelling as fish abundances underpin biomass and dollar value estimates
BRT output shows that the three most important variables with a combined relative contribution explaining around 80% of model variability were average current speed (32%), wave orbital velocity (26.4%) and monthly average sea surface tem perature at the time of sampling (21.5%) (Fig. 4)

Summary

Introduction

Marine fisheries play a key role in global food security, supporting coastal communities’ socio-economic well-being through recreational and commercial fishing and associated industries. The ecosystems that support fisheries production are fundamental for maintaining these contributions to societal well-being (Jennings et al, 2016; Mcclanahan et al, 2015). While it is understood that coastal ecosystems such as seagrass are vital to fisheries through habitat provision and food supply, the global distribution of these productive ecosystems continues to decline (Orth et al, 2006). Like fisheries production, are underpinned by various ecological processes such as habitat and food provision that are scale-dependent. Knowing variation in ecosystem service production at scales of interest to resource managers can help allocate resources and aid management practices – from regional to global perspectives (Lindborg et al, 2017). Most of the research on fisheries valuations was done at much larger scales, result ing in overlooking scale-dependent processes, potentially hindering fine-scale conservation decisions (Cole and Moksnes, 2016)

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