Marine Debris Project Final Report 2014

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8.2 Container Deposit: an effective policy for reducing litterCSIRO analysed a dataset on litter clean-ups provided by CleanUp Australia (CUA; www.cleanup.org.au) toevaluate whether there are any differences in the types of litter that are found among the states.Specifically, we asked whether sites in South Australia, which has a container deposit scheme, had fewerbeverage containers in the waste stream. CleanUp Australia provided counts of the number of items ineach of 94 categories across 750 sites in their 2012 clean-up (Table 1). Due to missing information fromsome records, we reduced the dataset down to 693 records. These records cover clean-ups from a widerange of sites, including parks, schools, beaches, waterways, etc. The CUA data does not includeinformation on the total area covered by a clean-up, nor does it include detailed information on the effort,aside from the number of people involved. Given these limitations, we chose to look at the relativefrequencies of beverage containers in the clean-ups as a metric of the effect of the container depositscheme. Beverage containers were restricted to seven of the 94 categories and included PET drinkcontainers, non-PET containers, alcoholic beverage bottles, soft drink bottles, fruit juice bottles, alcoholicbeverage and soft drink containers. Drink cartons, milk cartons, bottle caps and straws were not included asbeverage containers in this analysis.Table 2. The number of sites cleaned up in each state or territory as part of the 2012 Clean Up AustraliaDay activities. For a full listing of the 94 categories of items, please refer to the CleanUp Australia website(www.cleanup.org.au).Australian Capital Territory 7New South Wales 235Northern Territory 9Queensland 168South Australia 63Tasmania 29Victoria 127Western Australia 55We used regression analysis to compare the frequency of beverage containers with the frequency of otheritems in the clean-up data. We found that a model that included the state as an explanatory factor wassignificantly better than a model that assumed that the ratio of beverage containers to other items wasconstant nationwide based on Aikaike Information Criterion (AIC; constant everywhere: 61440, differ bystate: 54624). We examined the differences between the various states using a multiple comparison test toevaluate whether pairs of regression coefficients for each state were different.56 | Understanding the effects of marine debris on wildlife
Proportion of beverage containers0.0 0.1 0.2 0.3 0.4 0.5ababcdeffACT NSW NT QLD SA TAS VIC WAStateFigure 14. The proportion of beverage containers in materials recovered during clean-ups in Australia.Shaded bars depict the proportion of beverage containers in each state, error bars show the 95%confidence interval on these mean estimates. Bars which do not share a letter are significantly differentin a pairwise comparison at the p < 0.05 level.We found that beverage containers make up a significantly smaller fraction of litter in clean-ups from SouthAustralia, in comparison with the other states. While it would be preferable to be able to compare theseresults before and after the implementation of a container deposit scheme to look at its impactsHardesty et al. (<strong>2014</strong>) | 57
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OCEANS AND ATMOSPHERIC FLAGSHIPUnde
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Table of ContentsAcknowledgments ..
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FiguresFigure 1. Map depicting the
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AcknowledgmentsThis work was co-fun
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capacity and networks for educators
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Part IIntroductionMarine debris pos
Page 14 and 15: Figure 1. Map depicting the initial
Page 16 and 17: entanglement in derelict fishing ge
Page 18 and 19: What is next for the marine debris
Page 20 and 21: In year one of the project we carri
Page 22 and 23: encompassed the largest geographic
Page 24 and 25: fishing). Further information on th
Page 26 and 27: debris ingested by turtles to the d
Page 28 and 29: Some of our major research findings
Page 30 and 31: Part VSources, Distribution and Fat
Page 32 and 33: terrestrial sources to coastal debr
Page 34 and 35: component gives a measure of the re
Page 36 and 37: Figure 4. Debris density along the
Page 38 and 39: Figure 6. Map showing locations of
Page 40 and 41: Part VIThreat to Wildlife6. Overvie
Page 42 and 43: In order to facilitate an assessmen
Page 44 and 45: As human population growth continue
Page 46 and 47: Entanglements were primarily observ
Page 48 and 49: Part VIICitizen Science7. OverviewI
Page 50 and 51: immersion in a hands-on learning en
Page 52 and 53: Citizen science coastal surveysTran
Page 54 and 55: Figure 8. Map of Australia showing
Page 56 and 57: Figure 9. The mean density (items.m
Page 58 and 59: Sample sizes for all groups was low
Page 60 and 61: Figure 13. The relative abundance o
Page 62 and 63: It might be argued that survey task
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Page 68 and 69: collaboration with Ghostnets Austra
Page 70 and 71: Analysis of this survey data sugges
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Page 76 and 77: Part IXScience Communication9. Over
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Page 82 and 83: 13. Schuyler, Q, K Townsend, C Wilc
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Page 86 and 87: Le, H.H., Carlson, E.M., Chua, J.P.
Page 88 and 89: Schuyler, Q, K Townsend, BD Hardest
Page 90 and 91: Wilcox, C., Hardesty, B.D., Sharple
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Wealth from Oceans FlagshipCitation
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List of FiguresFigure 1. Map showin
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AcknowledgementsThis work is co-fun
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- Engage with industries contributi
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3 Accomplishments and achievements
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The map (below,) shows the relative
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Figure 4. Map showing locations of
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3.3 National data portal (improveme
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similar analysis to that described
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Figure 9. Tracks of turtle movement
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- Had their ghost nets marine debri
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2MCE radio. Indigenous rangers and
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In association with our Conservatio
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4 Anticipated achievements in Year
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Appendix E. Instructions for data e
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9) To enter your collection data, c
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3) Enter in the ‘surveyor details
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10) To enter your collection data,
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Appendix G. Marine Plastic Pollutio
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Appendix I. Global research priorit
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Appendix J. To Eat or not to Eat? D
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Appendix L. Mistaken identity? Visu
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Appendix Q. CSIRO marine debris pro
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CONTACT USt 1300 363 400+61 3 9545
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Marine Debris Project Final Report 2014

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