Philip Politis NRS 509, Fall 2003 Application of GIS in Marine Fisheries Trawl Surveys The goal of fisheries managers today is to achieve sustainability in our marine fisheries resources. Trawl surveys are an important aspect in assessing fish populations (stock assessment), their locations and habitat use. Data collected from trawl surveys are used to make important decisions on how to manage commercial and recreational fisheries and how to limit their rate of exploitation while maximizing the economic yield of the resource. For more than a decade the use of GIS in fisheries management has gained popularity and is growing rapidly. Applying GIS to trawl surveys is a promising avenue to better interpret collected data and to eventually better manage fisheries resources. Trawl surveys usually span large areas. This can be entire bays or estuaries, or in the National Marine Fisheries Service, Northeast Fisheries Science Center (NMFS, NEFSC) trawl survey, the entire east coast of the U.S. from Nova Scotia to Florida (Azarovitz, 1981). Historically, trawl survey data have been analyzed ignoring the spatial aspects or by analysis on geographically small scales (Issak and Hubert, 1997). However, with the advent of GIS and the widespread use of GPS on survey vessels, larger scale investigations of patterns of fish distributions and abundances, and how they change over time, are possible. Huge data sets are generated from trawl surveys. This is due to the frequency of the surveys, the number of trawls made each survey, and the many different species of fish identified in each trawl of the survey (Fortunati et. al., 2002). Also, the environmental parameters at each trawl station are incorporated into the data sets, such as temperature, salinity, dissolved oxygen, etc. The ability of GIS to graphically display and analyze layers of data as well as combine several layers together, makes GIS a powerful tool for dealing with the large amounts of data generated from trawl surveys (Issak and Hubert, 1997). This use of GIS in analyzing trawl survey data has great implications for habitat conservation and management. By overlaying fish abundance data from trawl surveys and essential fish habitat data in a GIS, fisheries managers are easily able to quantify suitable habitat for various species of fish as well as investigate how the habitat changes in size and shape over time and with different seasons (Stoner et. al., 2001). The use of GIS in this type of analysis quickly brings to light dynamic patterns in the data that would otherwise be missed, allowing fisheries managers to quickly identify and predict when and where the key habitats are for specific species of fish, such as nursery grounds, spawning grounds and areas of high/low prey abundance (Stoner et. al., 2001).
Most bottom trawl surveys avoid certain areas of the study region in which the trawl gear may be damaged or lost due to obstructions or rocky substrate (Zimmermann, 2003). However, these untrawlable areas are excellent habitat for certain species of fish, creating problems in determining the relative abundance of these fish (Zimmermann, 2003). Typically these untrawlable areas are identified by navigational charts, echo-sounding, underwater video, and word of mouth reports of locations of obstructions (Zimmermann, 2003). Using GIS to map untrawlable locations and then overlaying catch data from the trawl survey on top allows for the quantification of untrawlable areas within a survey region and to better estimate the relative abundance of fish species inhabiting the untrawlable areas. Within the fisheries community there is some debate as to the extent of damage done to the sea floor by trawl nets during surveys and more so in commercial use. The ability to quantify and assess the damage done by a trawl net is difficult. However, using GIS is a very useful method of doing so. Shirley (1997) was able to use a GIS to quantify the effects of the NMFS trawl survey and commercial trawlers on fish populations in the trawled areas. By overlaying trawling effort with catch data for a certain time period, the effect of trawling on specific areas can be quantified. The beauty of GIS in this analysis allows for the investigator to quickly query the data for any area he wishes and look at the effects of either commercial trawlers, the survey trawlers or combined trawling effort, and the effect that they may have on total fish biomass or a specific species of fish in that area. Trawl survey data are used to determine and implement management policies for fisheries resources. Usually, the surveys and policies are conducted and implemented by government agencies. It is no secret that commercial fisherman are somewhat skeptical of such policies and fisheries scientists are reluctant to incorporate their knowledge into policy making because it is thought of as unscientific. This is mainly because of the differences in their fishing methods. Commercial fisherman seek out large abundances of fish with very large gear and try to catch as much fish as possible, whereas surveys are designed to randomly sample large areas with smaller gear, even where fish are scarce (Brehme et. al., 2001). There remains a need in fisheries management to 1) Convey the scientific data to the community in a format easily understood and 2) Incorporate the vast knowledge of skilled commercial fisherman into the management of the fishery. GIS lends itself very well to this. Most fisherman are already skilled at interpreting geographic information because so much of their work is geographic in nature, as well as being skilled in the use of GPS (Brehme et. al, 2001). GIS is a great way of conveying the scientific survey data to the fisherman and can be done fairly easily via the internet. Adding skilled fisherman s knowledge of known locations of fish abundance into a GIS is a great way of enhancing the data collected from a trawl survey. It can also be a way of checking the survey method for accuracy and helping to predict future fish stocks.
As GIS technology continues to become more affordable and its use more widespread, the applications to fisheries trawl surveys will continue to grow. The ability of GIS to quickly and accurately display and analyze graphically large amounts of data make it a great tool for better interpreting and implementing data collected from trawl surveys. The incorporation of GIS into the planning of a trawl survey should increase, where a net can and cannot be set can now be more precisely located. I hope to see GIS used more for conveying complicated scientific data to the public in format more easily understood. As the use of GIS continues to grow in analyses of data collected from trawl surveys, more accurate assessment of fish stocks, fish locations and habitat use will emerge, eventually leading to a greater ability to manage our fisheries resources. Annotated Bibliography Brehme, C., A. Boyce, S. Henze, and B. Neal. 2001. Monitoring coastal fisheries in the Gulf of Maine with fisherman, GIS and the internet. Presented at CoastGIS 2001, Halifax, Nova Scotia, Canada This is an excellent paper. It is not concerned primarily with trawl surveys but with fisheries surveys in general, and its implications are very relevant to trawl surveys. The authors first describe the difficulties of using a GIS for analysis of the marine environment due its complexity and the need to incorporate the three dimensions of volume as well as time into the GIS. They then describe the difficulties of communication between scientist and fisherman and how GIS can be a means for better communication. The paper then describes three scenarios in which scientific studies were conducted along with local fisherman and GIS in the Gulf of Maine. Fortunati, L., G. Garafalo, and R. Demontis. 2002. TSDV: A GIS tool for inspection trawl survey data. ICES Journal of Marine Science, 59: 168-178. The authors of this paper do an excellent job of telling the reader about the complexities in the data collected from trawl surveys and how there is a definite need for the technology of GIS to aid in the analysis of such data. The focus of this paper is a tool developed from GIS that can be used by fisheries managers not familiar with operating a GIS, the Trawl Survey Data Viewer (TSDV). The TSDV is based on ArcView GIS 3.0 software and can take trawl survey data and geographically reference it in two dimensions (X, Y or latitude, longitude). The basic data that is geographically referenced are the locations of the hauls, both start and stop, and the location of the sample, which is essentially the midpoint between the start and stop of the haul. Species identifications are coded in the TSDV along with fish length (four classes), sex (m, f) and maturity (up to six classes). The main purpose of the TSDV is to allow non-gis fisheries managers a way of visually displaying the data, as well a run a limited amount of calculations on the data.
Issak, D.J. and W.A. Hubert. 1997. Integrating new technologies into fisheries science: the application of geographic information systems. Fisheries, 22(1): 6-10. This paper gives a great overview of what a GIS is, the components needed to successfully operate a GIS and how it can be applied to fisheries science. The need for GIS in analysis of large geographic areas of the marine environment is stressed and the paper shows how the use of data layers in a GIS can be used to analyze complex data sets together and visually display the results on a digital graph. There is also a nice section on where to go for certain types of data such as the Census Department for TIGER data or USGS for DLG s and DEM s. Marrs, S.J., I.D. Tuck, R.J.A. Atkinson, T.D.I. Stevenson, and C. Hall. 2002. Position data loggers and logbooks as tools in fisheries research: results of a pilot study and some recommendations. Fisheries Research, 58: 109-117. This article shows how GPS and GIS can be used together to graphically display the positions of trawl vessels. GPS position loggers were placed aboard commercial trawlers and the points were then downloaded into a GIS. The trawl paths of each vessel were mapped in vector format and then converted to raster images at a resolution of 0.121 km² pixel sizes. Pixels were then assigned and attribute of fished or un-fished (fished being a pixel in which the vessel passed though). Each fished pixel was then given a fishing effort value by dividing the total number of pixels fished by the time spent fishing. Catch data obtained from the fisherman s logbooks were then added to the GIS in raster format, allowing catch per unit effort (CPUE) to be easily calculated. The authors discuss how using different (higher) resolutions may provide more accurate calculations of CPUE. This use of GPS and GIS has great potential in other trawl surveys and for investigating previous trawl survey time series. Shirley, T. 1997. Retrospective analysis of the effects of trawling on benthic communities in the Gulf of Alaska and Aleutian Island region. http://www.cifar.uaf.edu/fish97/trawling.html. This article makes interesting use of a GIS in quantifying the effects of trawlers on the sea floor and fish populations. The authors investigate both commercial trawling fleets in the Gulf of Alaska and the National Marine Fisheries Service s (NMFS) west coast trawl survey. Fishing vessel location data from GPS, and catch data from NMFS observer programs were downloaded into a GIS using ARCVIEW (Arc/Info 1995). This allowed for analysis of trawl effort (location and duration of tows) both spatially and temporally. By overlaying the catch data, the effects of the trawlers on the fish populations could be easily calculated.
Stoner, A.W., J.P. Manderson, and J.P. Pessutti. 2001. Spatially explicit analysis of estuarine habitat for juvenile winter flounder: combining generalized additive models and geographic information systems. Marine Ecology Progress Series, 213: 253-271. This is a great paper on how GIS can be used to analyze trawl survey data to quantify habitat use. This study was able to use a GIS to define habitat use of age 0 winter flounder in Sandy Hook, New Jersey. The use of GIS gave the investigators a tool to quantify suitable habitat and identify patterns in how the size and shape of the habitat changes with seasons and over time. By overlaying catch data from the trawl survey with environmental parameters and plotting them graphically in raster format, the visual aspects of GIS made it easy to predict the dynamics of the habitat and when and where juvenile winter flounder populations may be found. To do this type of analysis without the aid of GIS would be a huge task and most likely the dynamic patterns of habitat use would not be identified. Zimmermann, M. 2003. Calculation of untrawlable areas within the boundaries of a bottom trawl survey. Can. J. Fish. Aquat. Sci. 60: 657-669. The study discussed in this article is an excellent application of GIS to fisheries trawl surveys. The investigators were able to use a GIS to calculate the amount of untrawlabe area in the National Marine Fisheries Service (NMFS) west coast trawl survey. Using ArcView (v. 3.2) the trawl events were classified and coded 1-4 by the quality of the haul. These data were then converted to a vector data set in the GIS and the investigators were able to quantify the amount of trawlable/untrawlable area within each stratum of the NMFS survey. Interestingly, the study was able to obtain more precise estimates of relative biomass for rock-fish, Sebastes Spp., a species that aggregates in rocky areas that are difficult to trawl. Other References Azarovitz, T.R. 1981. A brief review of the Woods Hole Laboratory trawl survey time series. In: Bottom trawl surveys, W.G. Doubleday and D. Rivard Eds. Canadian Special Publication in Fisheries and Aquatic Sciences, 58: 62-67. Meaden, G.J. and T.D. Chi. 1996. Geographical information systems applications to marine fisheries. FAO Fisheries Technical Paper 356 Walunda, C.M. and G.J. Pierce. 1998. Temporal and spatial patterns in the distribution of squid Loligo spp. in United Kingdom waters. South African Journal of Marine Science, 20: 323-336.