Integrating ecology, oceanography and genetics for spatial fisheries management

Krück, Nils C. (2013). Integrating ecology, oceanography and genetics for spatial fisheries management PhD Thesis, School of Biological Sciences, The University of Queensland.

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Author Krück, Nils C.
Thesis Title Integrating ecology, oceanography and genetics for spatial fisheries management
School, Centre or Institute School of Biological Sciences
Institution The University of Queensland
Publication date 2013
Thesis type PhD Thesis
Supervisor Ian Tibbetts
Jennifer Ovenden
Eric Treml
Hugh Possingham
Total pages 175
Total colour pages 4
Total black and white pages 171
Language eng
Subjects 0704 Fisheries Sciences
0602 Ecology
0405 Oceanography
Formatted abstract
Overfishing has caused substantial depletions of fish stocks worldwide, culminating in the collapse not only of fisheries but entire coastal ecosystems. Consequently, there have been calls to set aside a significant share of the world’s oceans as marine protected areas (MPAs), which restrict certain or all types of fishing within their boundaries. The relatively recent global implementation of MPAs that followed initiated an unprecedented level of scientific attention to the spatial dimensions of fish and fisheries. Following several years of research, there is wide scientific consensus that MPAs are useful conservation tools, helping to rebuild degraded habitats and to protect ecosystems and biodiversity. However, a lack of knowledge about the movements of fish as larvae and adults commonly impedes accurate predictions of the efficiency of MPAs as fisheries management tools. In situations where MPAs may be very suitable (e.g. in case of high management uncertainty, low management capacity or low profit and multi-species fisheries) even the most fundamental information for accurate evaluations is sometimes lacking. This includes basic information on the spatial distribution and catch of fishery species. Recent advances in genetic technology along with an increasing availability of spatial information on species and environments promise new research opportunities through integrated analyses that could supplement spatial fisheries management assessments in such difficult situations. My thesis comprises six chapters that are concerned with this topic in the form of reviews, case studies and simulations.

The first chapter of my thesis is a general introduction delineating in more detail the problems outlined above. It continues by describing the situation of inshore fish and fisheries in south-east Queensland (SEQ), Australia, which inspired studies presented in chapters 3-5. Eastern Australian fisheries also triggered a review included as Chapter 2, which outlines key characteristics and current uses of recent genetic technologies, associated research trends, and implications for applied fisheries management and conservation. Chapter 2 is focused on sharks and rays, but equally valid for various other non-model fisheries species. Chapters 3 and 4 continue with two case studies on eastern Australian sea mullet (Mugil cephalus), addressing concerns about cryptic speciation, overlooked population structure and uncertain migration patterns of this ecologically and economically important fisheries species.

Chapter 3 concentrates on the application of next generation sequencing (NGS) to identify single nucleotide polymorphisms (SNPs) among M. cephalus along the eastern Australian coastline. Based on 161 of these SNPs, validated by genotyping 63 DNA samples, I analyse spatial genetic variation in relation to coastal geomorphology and presumed temperature requirements. The findings demonstrate that (i) even limited NGS and SNP genotyping can allow for ascertaining the range of data-poor fishery species based on integrated spatial analyses. Simultaneously, (ii) the results suggest a hitherto unknown cryptic species in northern QLD, which causes a mixed fishery.

In Chapter 4, I establish a new indirect method for estimating fish movements based on coupled oceanographic-genetic simulations. The idea behind my approach was that larger scale movements of fish, which are most relevant for spatial fisheries management arrangements, are frequently related to spawning activity. Assuming that the dispersal of pelagic fish eggs and larvae with ocean currents varies depending on spawning destinations, there may be a traceable spatial profile in recruitment and genetic deviation indicative of migration routes. Chapter 4 describes in detail the concept and implementation of this migration-dispersal profiling approach using a case study on M. cephalus. Based on a subset of previously identified SNPs and 692 additional DNA samples from various estuary locations, I test several conceivable spawning migration hypotheses by contrasting simulated and observed patterns of spatial genetic variation. Interestingly, the results suggest inshore spawning destinations ≤100 km north of origin estuaries as predicted based on past capture-mark-recapture and parasite studies as well as oceanographic conditions.

In Chapter 5, I use a spatial model to simulate variable fish movements, fisher behaviours, reserve network designs and MPA scenarios in order to assess fisheries management efficiency. Explicitly, this chapter is concerned with the situation of moderately to highly mobile target species, which were the focus of debates about recent MPA extensions in SEQ. The model confirms that largely sedentary species can be efficiently protected with MPAs, and that fishery benefits through excess recruitment will depend on reserve configurations relative to larval dispersal distances. Highly mobile target species and fisheries are found to be insensitive to MPA implementation as expected. Concerning moderately mobile target species, however, which were of particular interest, the results show how important realism and case-by-case evaluations will be for reliable predictions of MPA impacts on fish and fishers. In Chapter 6, I conclude with a brief reflection on my work and potential future research opportunities.
Keyword Marine ecology
Fisheries management
Population genetics
Biophysical modelling
Population connectivity
Marine reserves network
Next-generation sequencing
Seascape genetics

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Created: Thu, 21 Nov 2013, 09:55:26 EST by Mr Nils Krueck on behalf of Scholarly Communication and Digitisation Service