Erin McLean NRS 509 GIS Applications in Commercial Fisheries Focus on: Lobster

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1 Erin McLean NRS 509 GIS Applications in Commercial Fisheries Focus on: Lobster The management of the lobster fishery has largely been taken care of by the fishermen themselves over the past century. V notching, the practice of marking an ovigerous female so that she continues to reproduce, has been common practice since the early 1900s. More recently, state departments of fish and wildlife have gotten involved (still with fishermen input) and implemented a double sided gauge: the smaller lobsters and the larger lobsters get thrown back to either grow more or reproduce more. It wasn t until recently that these conservation tools have been joined by a new tool GIS mapping that has the potential to tell fishermen and managers alike a lot about the lobster populations that are currently heavily exploited. One of the most basic applications of GIS to the lobster fishery is to determine the optimal habitat for lobsters, then map where that habitat is located in a particular region. So far, optimum habitats have been determined for both Homarid lobster fisheries using spatial analysis tools: American lobster (Chang et al., 2010; Dunnington et al., 2005) and European lobster (Galparsoro et al., 2009). In all three studies, the authors set out traps in different habitat types that were referenced to GPS coordinates. From there, they were able to record the biological data of the lobsters caught (usually size and sex), georeference them to a map of the seafloor, and determine how many lobsters of each sex and size class were caught in each habitat type. The major limitation on this type of study is that traps are not necessarily the best proxies for the lobster population in an area because traps are designed for commercial fisheries, often smaller lobsters escape. One study remedied that problem by using traps without the escape hatch, and were able to report optimum habitats for both adults and juveniles (Dunnington et al., 2005). Another way the power of GIS has been harnessed in the lobster fishery is to evaluate the effectiveness and impact of marine protected areas (MPAs). In an effort to conserve the fishery, MPAs have been established to provide a refuge for exploited lobster species. One early study evaluated whether these MPAs are effective that is, whether or not the lobsters found inside the borders are larger than the ones found outside. The study was only done three years after the establishment of the MPA, but she found that the lobsters inside were in fact slightly larger than their counterparts outside (Rowe, 2002). That find hints at a promising future for lobsters and for MPAs, but more work would need to be done on whether or not the eggs from the lobsters in the MPA spread to outlying areas, ensuring the continuation of the fishery. GIS and remote sensing techniques could be harnessed to fill that need. If it is established that MPAs work for the lobster population, more work will need to be done on how that impacts the local fishermen. The prevailing notion is that once an MPA is established in the range of an exploited species, fishermen will fish the line or along the border of the MPA. The idea is that the target species doesn t know where the MPA line is, so there s nothing to stop it from going over into a net or a trap. Researchers in California set out to see how fishery pressure changes before and after MPAs were established: did fishermen fish the line, or did they move to other territories? The only study on this to date was creative in its use of GIS technology: these researchers had the fishermen draw their territories, and they were able to georeference them to NOAA charts using local landmarks (Guenther et al., 2015). From there, they were able to estimate with coarse spatial resolution how much pressure had changed in the area before and after the establishment of the MPA, and they found that those fishermen are not fishing the line rather, they re concentrating their efforts away from the MPA. Some fishermen gave their reasoning fear of fines, just not catching lobsters there but it would be interesting to repeat this study s methodology for other marine protected areas and other exploited species to understand how MPAs are impacting the fishermen. Finally, the lobster fishery is unique in that it can create large amounts of marine debris in the form of lost traps. It s common for fishermen to lose traps, and those ghost traps can cause problems for local benthic communities by altering the habitat or community structure. One study set out to use GIS to map hot spots where those traps are likely to accumulate, using currents and habitat mapping, so that contract debris collectors could maximize their clean up efforts (Martens and Huntington, 2012). They were able to link high densities of lost traps to seagrass habitat at a depth of 3-4 m, but they recognized the limitations traps could be lost in a group, and are usually initially released in seagrass beds to catch lobsters. However, they did successfully create a model that is likely to inform future clean up operations. Other regions of the fishery would benefit from a similar

2 analysis. Because GIS is a relatively new tool in an old fishery, applications of the technology are only beginning to take hold in labs near lobster-heavy regions. In the future, there are likely to be more comprehensive studies aiming to understand the fragile equilibrium of the fishery: understanding the distribution and settlement processes of all life stages and how that relates to landings and catch per unit effort are just two of the many directions this research could take. In understanding distribution and settlement, the most important knowledge gap that must be filled is where eggs are hatched and where they end up settling. The fishery depends on the larvae today to sustain the fishery ten years from now, and not having a full understanding of those processes leaves the fishery vulnerable to a crash. While not much has been done so far, studies are beginning to investigate questions pertaining to larval dispersal using spatial analysis tools. One study has tagged male and female American lobsters and monitored their migration in part to determine how far offshore females migrate before they hatch their eggs and whether they move towards shore to release them (Goldstein and Watson, 2015). Their results were inconclusive, though, and the authors didn t focus on the eggs themselves. No studies to date have used GIS technology to look at larval dispersal. In a fishery with such a large time lapse between hatching and capture, this should be a major concern going forward for managers and fishermen alike. Annotated Bibliography 1. Chang, J.-H., Chen, Y., Holland, D. and Grabowski, J. (2010). Estimating spatial distribution of American lobster Homarus americanus using habitat variables. Mar. Ecol. Prog. Ser. 420, In this paper, Chang et al. modeled lobster habitat along an environmental gradient in order to better understand the population distribution for future management decisions and to protect essential fish habitat. They developed season-, size-, and species-specific models for the distribution of the species. For the environmental data (salinity, temperature, depth, sediment type, etc.) they used models already in place, created by the Gulf of Maine Ocean Observing System, and for the density data, they used data from the Maine-New Hampshire Inshore Trawl Survey. They then Kriged the data to create continuous raster maps with a cell size consistent to both the environmental and the density data. The model was able to find the most likely conditions for the lobsters, and then they were able to map the likely habitat areas produced by their model using GIS. They acknowledged the limitations of the trawl survey data mainly, the trawl is unable to function on rocky sediments and that could have skewed the data. The paper is well presented, though, and adds an important tool for managers working in the Gulf of Maine on this high-value fishery species. 2. Dunnington, M. J., Wahle, R. A., Bell, M. C. and Geraldi, N. R. (2005). Evaluating local population dynamics of the American lobster, Homarus americanus, with trap-based mark-recapture methods and seabed mapping. New Zeal. J. Mar. Freshw. Res. 39, In this paper, Dunnington et al. used both remote sensing and GIS techniques to map the densities of lobster in different habitat types. They used seabed mapping (through side-scan sonar) and diver surveys in conjunction with mark and recapture methods to evaluate what habitats were preferred and what habitats trapped the most lobsters. They set traps and spatially referenced them through GPS so that they could match the trap sites to the side-scan sonar data, which gave them the habitat type: bedrock, cobble, or sediment. The side-scan sonar images were put into ArcView and stitched together to form a mosaic. From the mosaic, then, the researchers could calculate the area of the seafloor associated with those three habitats. The traps and diver surveys provided the number of lobsters caught in the area, so the number of lobsters combined with the area of the habitat could then be presented as the density. They found that most juvenile lobsters were caught in sediment traps but were seen more often in cobble, and that adult lobsters were as likely to get caught or be seen in any of the three habitat types. This study acknowledged the various limitations and sources of error in their methods, but stressed the importance of their study as a robust way to understand where these lobsters of both size classes were hiding and being caught.

3 3. Galparsoro, I., Borja, Á., Bald, J., Liria, P. and Chust, G. (2009). Predicting suitable habitat for the European lobster (Homarus gammarus), on the Basque continental shelf (Bay of Biscay), using Ecological-Niche Factor Analysis. Ecol. Modell. 220, In this paper, Galparsoro and colleagues set out to identify the seafloor and wave energy conditions that determined the presence of European lobster in the Bay of Biscay. Predicting habitat distributions is important for management decisions, but no one had done a study like this for the European lobster, likely because of the poor seafloor data available. Galparsoro and colleagues righted that lapse in data by mapping the bathymetry and the backscatter data (determined seafloor type) using multibeam echosounders. From the echosounder data, they were able to use ArcGIS to identify 10 different bottom types, the aspect of each pixel (important for considering wave energy), and the benthic position of each pixel (whether it is part of a crest or trough). To that data they linked biological data obtained from GPS-linked trap samples. From there, they could find out which habitat type was more likely to have lobsters, which they determined to be near sediment and rocky bottom boundaries. Next, they created an index called habitat suitability. Habitat suitability uses matrix addition and calculates a value for each pixel from 0-1, with high values meaning that the local environment the lobster is in is close to the optimal environment. They could then map all the optimal conditions, and used their model of habitats obtained from the multibeam echosounder data to create a map of habitat suitability, essentially informing managers where in the Bay lobsters were most likely to be found. This research seems extremely meticulous and complete, and the authors validated their models with several different tests before concluding that they were successful in most cases. To that end, this method seems like a valuable resource for managers of the European lobster fishery, and could be adapted to all commercial fisheries that have animals with a specific habitat preference like the lobster. 4. Goldstein, J. S. and Watson, W. H. (2015). Seasonal movements of American lobsters in southern Gulf of Maine coastal waters: patterns, environmental triggers, and implications for larval release. Mar. Ecol. Prog. Ser. 524, In this paper, Goldstein and Watson looked at the seasonal migration of lobster in order to figure out why these animals undergo a seasonal migration. The leading hypothesis is that they migrate so that they have more warm days, which increases their growth rates and, for ovigerous females, egg development times. To see if that s the reason, the researchers tagged 45 lobsters in diverse sizes and across three categories: male, non-ovigerous female, and ovigerous female. They used ultrasonic telemetry to tag these lobsters and three levels of resolution in their sensing: low resolution, from stationary receivers; medium resolution, from a mobile sensor towed behind a boat; and high resolution, from a fixed array radio-acoustic positioning system (VRAP). They were able to log the locations of each tagged lobster throughout the year from fall to early summer. Once they downloaded the data from the tags, they uploaded it into ArcGIS and calculated the distance moved by taking the point from each season that would yield the highest distance. They found that females did travel more distance than males, sometimes dramatically more. They were able to plot the locations on a map to visually represent the difference between an ovigerous female s migration and a male s lack thereof. However, the researchers couldn t connect this movement to the release of eggs: ovigerous females moved more distance, but it wasn t always towards shore in the early summer, and if it was, it was after the predicted hatch period. Because that result was inconclusive, there is still not much known about where lobsters hatch their eggs or why they choose whatever location that is. The authors concluded that it warranted further study, as the patterns of egg dispersal greatly influence larval survival and the future of the fishery. Remote sensing and GIS techniques combined would be a great way to answer those further questions. 5. Guenther, C., López-Carr, D. and Lenihan, H. S. (2015). Differences in lobster fishing effort before and after MPA establishment. Appl. Geogr. 59, In this paper, Guenther and colleagues did something entirely new: rather than map the habitat of lobsters to determine whether the marine protected areas (MPAs) in California are working for the spiny lobster fisheries, they aimed to see if fishermen were able to reap the benefits of an MPA by fishing close to the borders. The adaptive approach of fishermen to fish the line has been seen in Maine and the Mediterranean, but the authors wanted to see if that was a valid strategy in the California system. To do that, they mapped 10 years of data obtained from fishermen s logbooks, five years before the implementation of the MPA and five years after. They

4 created a map of the fishermen s territories from interviews with fishermen that had them draw their fishing territories in reference to local landmarks. From there, they created a shapefile that had polygons of all the territories, and that data was linked to the logbook entries of how many lobsters were caught at that place over the 10 years. They assigned each polygon as being on the border of the MPA or not based on location parameters (their centroid had to be 1 km away from the border to be considered border) and determined the trap density, total traps, and percent change in traps before the MPA and after the MPA for each one. They found that fishermen in the California spiny lobster fishery are not aggregating their effort at MPA boundaries the percent change at most of the border polygons was negative for the five years after the MPA. Some of the reasons given were that it wasn t worth it in terms of catch per unit effort, suggesting that lobsters are not spilling over from the MPA to open waters, or that it wasn t worth it in terms of the prohibitive fines that can be levied if a fishermen s pots are located too close to the boundary of the MPA. This study was particularly interesting to me because they created their own dataset based on hand drawn maps by the fishermen while this decreased spatial resolution (which the authors acknowledged), it represents a respect for fishermen s knowledge not normally seen in science. The authors acknowledge more of the limiting factor CPUE changes from year to year, fishermen hemmed in by habitat suitability, etc. but this study challenges the commonly held assumption that fishermen will fish near MPAs and reap the spillover effects that managers and fishermen alike should pay attention to. 6. Martens, J. and Huntington, B. E. (2012). Creating a GIS-based model of marine debris hot spots to improve efficiency of a lobster trap debris removal program. Mar. Pollut. Bull. 64, In this paper, Martens and Huntington combined five years of lobster trap debris removal data with remotely sensed habitat and bathymetric data to try to create a map of hot spots, places where these ghost traps accumulate. The goal of any ocean clean up effort is to maximize the efficiency of the debris removal, and by identifying these hot spots, the authors hoped to inform future debris removal efforts. These traps cause a problem because even after fishermen no longer monitor them, they continue to trap animals (even those other than the intended species) while also disrupting the habitat and sometimes the food web of the area. They used inverse distance weighting to determine the bathymetry of the region, which allowed them to create a continuous raster dataset from a point shapefile. They then used the spatial analyst tool to extract data from the raster files and match it to the locations where an independent contractor had previously collected debris. They encoded each habitat pixel with a number from 1-14 based on how often traps were found in that habitat (e.g. seagrass, cobble) and each depth pixel with a number from 1-13 (e.g. 0-5 m, 5-10 m) also based on frequency of occurrence. They then used map algebra to combine the two values so that each pixel had a value from 1-27, with higher numbers meaning that the debris was more likely to be found there. From there, they could produce a map of the region showing the most likely depths and habitats where those traps would end up allowing the independent contractors to use the maps to focus future clean up efforts. 7. Rowe, S. (2002). Population parameters of American lobster inside and outside no-take reserves in Bonavista Bay, Newfoundland. Fish. Res. 56, In this paper, Rowe set out to evaluate the effectiveness of two no take reserves on the lobster populations three years after they were established in Newfoundland, Canada. Her specific objectives were to determine the amount of lobster habitat present in these reserves and to compare the biological characteristics of the lobster populations (sex ratio, size, density) to nearby open areas. For that first objective, she mapped the habitat available to lobsters using digitized data from aerial photos, georeferenced to topographic maps and digital bathymetric terrain models. The boundaries of the reserve were determined as the shoreline of the island and the edge of the continental shelf, which was determined by GPS coordinates taken on a boat. Those coordinates were put into a GIS and the reserve could then be mapped over the aerial photos. She was then able to determine, after a three year catch and release study in which she caught lobsters and recorded GPS coordinates as well as biological data, population density and size differences between the reserves and the open habitat. While she reported that population size, density, and female: male ratios were higher in the protected reserves, she does mention the limitations on her study: traps themselves are limited as population estimators, as they only catch a subset of lobsters, and that it s possible that the reserve sites already had a robust population of lobsters

5 even before the reserves were established. Because this size class of lobster is molting approximately twice in that period of time, increasing size by ~15% or so each time, I don t think her results for size differences are valid. However, her habitat mapping work and method for determining the population density of the lobsters seem to be consistent across the four sites, and I trust that data more.