Classifying Marine Protected Areas: A global, regulation-based approach

to evaluate MPA management and ecological and socioeconomic factors

by

Gia Mancini

Dr. David Gill, Advisor

April 24, 2020

Masters project submitted in partial fulfillment of the

requirements for the Master of Environmental Management degree in

the Nicholas School of the Environment of

Duke University

Executive Summary

Marine Protected Areas (MPAs) are a widely used method to protect fisheries, ocean resources, and areas of cultural significance. In recent years, they have garnered increased global support as an effective conservation and management strategy. MPA regulations and management strategies vary widely across the globe and even within MPAs themselves.

This project aims to classify MPAs based on fishing gear regulations within MPA zones and examine the relationship between regulations and the surrounding social and ecological context.

We compiled data on 280 zones in 125 MPAs in 24 countries, classifying MPAs based on their estimated impact of allowed fishing activities. MPA gear regulations varied greatly, with impact scores ranging from 0-9. Overall MPA index classification scores varied from 0-7, with an average score of 3.1. With these data, we assess the relationships between MPA fishing restrictions and the surrounding socio-environmental context. Out of

25 socio-environmental datasets, only two factors were significantly correlated with MPA index classification scores at the 5 percent level. Infant mortality had a weak positive correlation and perceived level of corruption had a weak negative correlation. However, these relationships are likely spurious as there is no clear causal relationship between these variables.

This project has revealed issues of inconsistency in the reporting of MPA fishing regulations between MPAs. This makes it challenging to assess which MPA regulations and management strategies are the most effective at protecting ocean resources. This study underscores the need for a global, streamlined database on MPA fishing regulations to better inform more effective MPA management and data collection methods.

2 Table of Contents

i. Introduction…………………………………………………………………………………………………4

ii. The Horta e Costa et al. MPA Classification System……………………….…..……………6

iii. Objectives…………………………………………………………………………………………………….7

iv. Data……………………………………………………………………………………………………………..8

v. Materials and Methods…………………………………………………………………………………10

a. Fishing Regulations Data.……………………………………………………………….….10

b. Fishing Gear Scores.……………………………………………………………….…….……11

c. MPA Zone Classification Scores..…………………………………………………..….…12

i. Allowed Maximum Zone Scores…………………………………………….…12

ii. Banned Minimum Zone Scores………………………………………..….……13

iii. Combined Scores………………………………………………………………….…14

d. MPA Index Classifications..………………………………………………...…….…………16

e. Geospatial Analysis…………………………………………………………………………….17

f. Statistical Analysis……………………………………………………………………………..17

vi. Results…………………………………………………………………………………………………………18

a. Global MPA Index Classification Results………………….…………………………..18

b. Regional MPA Index Classification Results………………….……………………….19

c. Threatened Areas of Importance…………………………………………………………21

d. Statistical Results………………………………………………………………………………..22

vii. Discussion……………………………………………………………………………………………………..22 viii. Conclusion…………………………………………………………………………………………………….26

ix. Appendix………………………………………………………………………………………………………28

x. References…………………………………………………………………………………………………….40

3 Introduction

Marine Protected Areas (MPAs) are a widely used method to protect fisheries, ocean resources, and areas of cultural significance. In recent years, they have garnered increased global support as an effective conservation and management strategy. However, there is little research on the relationships between MPA regulations and the ecological and socioeconomic context they are situated in. It is important to study MPAs and regulations to better understand the most effective management strategies in order to better protect ocean ecosystems and resources that both humans and animals rely on.

MPA regulations and management strategies vary widely across the globe and even within MPAs themselves. MPAs can be divided into zones based on the activities permitted in each zone. For example, some MPAs are no-take and prohibit fishing all throughout the

MPA, while other MPAs are multiple-use and allow fishing either throughout the entire

MPA or only in certain zones. Restrictions may not only be placed on the locations within the MPA that fishing is permitted, but restrictions may also be placed on the seasons in which fishing is allowed, the type and number of fish that may be extracted, and the fishing gear that may be used. Many MPAs also designate areas that allow for swimming, snorkeling, and diving, as well as education and research. To inform future MPA creation and zoning, it is important to determine the regulations and management strategies that lead to successful ecological and socioeconomic outcomes.

This project aims to classify MPAs based on fishing gear regulations, and examine the relationship between regulations and the surrounding social and ecological context.

The goal of this project is to build a more complete picture of MPA fisheries regulations worldwide and the ecological and socioeconomic context they are situated in.

4 Multiple studies have demonstrated the increased effectiveness and ecological success of more strict over less strictly regulated MPAs. A study conducted by Campbell et al. (2017) across 22 MPAs showed that no-take MPAs (most strict form of fishing regulations) resulted in the greatest increase in fish biomass when compared to areas where fishing was permitted with gear restrictions and areas where fishing was openly permitted. Studies by Lester et al. (2008) and Zupan et al. (2018) have also shown the ecological benefits of no-take MPAs over multiple-use MPAs.

A study conducted by Selig et al. (2018) determined that over 775 million people worldwide live in areas that are highly dependent on marine ecosystems for economic and nutritional needs. A mounting concern around the world is how to sustainably harvest fish stocks in order to feed a growing population and sustain the livelihoods of those in coastal communities. Many fisheries are over-exploited and depleted, and run the risk of collapse.

MPAs can play an important in role in preventing these occurrences, but only if the proper regulations are in place and backed by enforcement and compliance (Edgar et al., 2014).

Another study conducted by Selig et al. (2017) demonstrates the importance of determining successful and unsuccessful management tools in order for an MPA to be effective and provide the expected ecological and socioeconomic benefits.

By determining and applying the most effective management strategies and regulations, MPA ecological and socioeconomic outcomes will likely improve. Increased

MPA success will create healthier environmental conditions that allow fish to breed and flourish, while also providing protection for threatened species and ecosystems. Increased fish stocks in conjunction with sustainable harvesting should result in economic and

5 nutritional benefits for those whose livelihoods depend on the oceans and coasts (Aswani and Furusawa, 2007).

The Horta e Costa et al. MPA Classification System

This project builds off of the foundation created by Horta e Costa et al.’s “A regulation-based classification system for Marine Protected Areas (MPAs)” (2016). Horta e

Costa et al. created a classification system that assesses regulations within MPA zones on a numerical scale of 1 to 9, with 1 being the least impactful fishing gear and 9 being the most impactful and destructive fishing gear The Horta e Costa et al. paper examined and scored

21 different types of fishing gear (Figure 1).

Figure 1. This chart was obtained from Horta e Costa et al. (2016). The chart displays the fishing gear assessed in the study and the assigned gear scores. The scores range from 1, least impactful, to 9, most impactful and destructive.

The MPA is then evaluated using an MPA index equation to determine the level of protection provided by the entire MPA on a categorical scale from 1, fully protected, to 8, unprotected. This is done by accounting for the different zones within an MPA, their

6 individual levels of regulation and protection, and the area occupied by each zone (Figures

2A and 2B). Horta e Costa et al.’s work is just one example of an MPA classification system.

A classification system for MPAs in the United States was created by NOAA and classifies

MPAs based on their level, permanence, constancy, and scale of protection and conservation focus (Wenzel and D’lorio, 2011).

Figures 2A and 2B. These graphics were obtained from Horta e Costa et al. (2016). The graphics display the Horta e Costa et al. regulation-based classification system calculations and classification scheme. Figure 2A shows the zone classification system and Figure 2B shows the MPA classification system.

Objectives

This project aims to expand upon and apply Horta e Costa et al.’s classification system to MPAs globally. In this project we examine 280 zones in 125 MPAs in 24 countries. The main objectives of this project are to:

7 Ø Classify the level of protection of MPAs based on their fishing regulations

Ø Examine the variation in levels of protection globally

Ø Examine the relationship between MPA level of protection from fishing and a suite of

ecological, social, and economic contextual factors

Exploring the correlations between MPA distribution, level of protection, and ecological and socieconomic factors will provide insight into how well MPAs are protecting the most vulnerable ocean and coastal areas, and on the other hand, how restrictions could be affecting dependent coastal communities. Noticeable variations and trends in spatial distributions of MPA regulations and factors across regions will help to better inform the creation and management of future MPAs.

Data

The Gill Lab’s MPA database was used to obtain information regarding the MPA regulations and design attributes, such as what gear are allowed and banned, if there are seasonal or species restrictions, and if the MPAs are zoned. The MPA data comes from research articles, management plans, and MPA maps for each MPA. The ecological, social, and economic contextual data in this study (Table 1) was grouped into four main categories: Environmental, Social, Threat Level, and Management Capacity. The

Environmental category focuses on environmental factors within the MPA area; the Social category focuses on characteristics of the population surrounding the MPA and the extent to which the population relies on the MPA for resources and economic revenue; the Threat

Level category focuses on the climate risk to the country and the country’s ability to adapt to climate change; and the Management Capacity category focuses on fisheries and environmental management within a country.

8 Spatial Data Source Year Datasets Coverage Resolution

Environmental Datasets

Dryad 2017 • Marine Biodiversity 1 decimal degree Global Mapping Ocean Wealth Explorer, 2014 • Coastal Environment Status Country Level Global Coasts at Risk • Environmental Indicators (Tropics) World Resources Institute 2011 • Reefs at Risk Revisited 500 meters Global

Social Datasets

CIA Factbook 2017 • Infant Mortality Country Level Global Food and Agriculture 2017 • Seafood Consumption Per Country Level Global Organization of the United Capita Nations Mapping Ocean Wealth Explorer, 2014 • Percent Undernourished Country Level Global Coasts at Risk People • Percent Extreme Poverty Marine Economic Revenue • Percent Animal Protein from Fish United Nations 2019 • Human Development Index Country Level Global • Life Expectancy at Birth • Expected Years of Schooling • Mean Years of Schooling • Gross National Income Per Capita World Bank 2018 • Gross Domestic Product Country Level Global World Bank 2017 • Population Country Level Global World Bank 2016 • International Tourism, Country Level Global Number of Arrivals

Threat Level Datasets

Mapping Ocean Wealth Explorer, 2014 • Susceptibility Country Level Global Coasts at Risk • Vulnerability • Lack of Adaptive Capacity • Lack of Coping Capacity • Coastal Exposure • Coasts at Risk Index

Management Capacity Datasets

Mapping Ocean Wealth Explorer, 2014 • Fish Management Country Level Global Coasts at Risk Effectiveness • Corruption Perception Index

Table 1. This chart displays the datasets used in this study divided into 4 categories: Environmental, Social, Threat Level, and Management Capacity.

9 Materials and Methods

Fishing Regulations Data

The fishing regulations data varies widely from country to country, and even from

MPA to MPA. The fishing regulations data collected include: whether traditional, recreational, or commercial fishing is allowed; which gear types are allowed and banned; whether or not there are area, temporal, or species restrictions on fishing. While some

MPAs have an explicit and detailed list of the regulations and fishing gear that are allowed and banned within each MPA zone, some MPAs only have a general list, while others have no information at all. In certain cases where there was little to no information, the Gill Lab spoke with MPA managers and were able to gain an understanding of the regulations and gear used within the MPA.

The MPA fishing regulations data from the Gill Lab’s database was assessed based on level of confidence that the data source and data was reliable and accurate. Only MPAs with high levels of confidence were used in the analysis. Due to a lack of consistent data reporting on fishing gear regulations across MPAs globally, the analysis was further narrowed down based on data availability. Only MPAs with either data on allowed fishing gear, banned fishing gear, or both were included. Level of confidence and data reporting reduced the number of MPAs in this analysis from over 160 to 125 MPAs. Despite the reduction in MPAs that could be used in this analysis, the 125 remaining MPAs still cover multiple marine regions globally, with many of them clustered in coral reef areas in the

Caribbean and Western Pacific (Figure 3 and Table 2).

10

Figure 3. This map displays the global distribution of the 125 MPAs used in this study.

Marine Region Number of MPAs Caribbean 49 Indian Ocean 8 Mediterranean 2 North Atlantic Region 1 Northern Pacific Region 10 Western Pacific Region 55 Table 2. This table displays the number of MPAs within each marine region.

Fishing Gear Scores

As in the Horta e Costa et al. study, this study examines MPA level of protection based on level of protection from fishing gear. The Horta e Costa et al. study included 21 gears, while this study includes 67 gears (Appendix, Table 1). The fishing gear scores were ranked on a scale from 1 to 9, from least destructive or low impact to most destructive or high impact. These scores are based on species and size selectivity and habitat impacts. The assigned gear scores used in this analysis come from the Horta e Costa et al. paper. The gear scores for the gear that were added in this study were informed by and determined in

11 consultation with Horta e Costa. In some cases, gear was permitted, but there were gear restrictions. For example, certain gears like hook and line fishing were permitted in an MPA zone, but were only allowed within a specified distance from shore. Since this reduces the gear’s impact on the MPA, we reduced the score for that gear within that zone by 20 percent.

MPA Zone Classification Scores

The Horta e Costa et al. paper solely looked at allowed fishing gear within MPAs.

This study examines both allowed and banned fishing gear within MPAs. The main reason for looking at both allowed and banned fishing gear is due to differences in data reporting.

Out of the 125 MPAs used in this study, 41 of the MPAs are multiple zone multiple use

MPAs, 41 are single zone no-take MPAs, and 43 are single zone multiple use MPAs. Out of these MPAs, 20 have only allowed gear data, 17 have only banned gear data, and 88 have both allowed and banned gear data. As a result, we had to calculate two different types of

MPA zone scores – the allowed maximum score and the banned minimum score (Appendix,

Table 2).

Allowed Maximum Scores

The allowed maximum score focuses on the highest and most destructive gear score within each zone. This is the score the Horta e Costa et al. paper looked at, the gears that were permitted in each MPA zone based on their level of destructiveness. The allowed maximum score directly translates into the zone classification score based on the most destructive gear permitted within the MPA zone. The highest and most destructive gear score within the MPA zone is the allowed maximum score. If there is only one gear permitted in a zone, then the gear score of that gear is automatically the allowed maximum

12 score. For no take zones where no fishing is permitted, the allowed maximum score is automatically 0 since no gear are allowed. Therefore, the higher the zone score, the more destructive activities are permitted within the MPA zone. Figure 4 below provides an example of how the allowed maximum score is calculated for different types of MPA zones.

Figure 4. This graphic provides an example of the allowed maximum zone scoring for a zoned MPA. The purple zone allows 3 different gear types, and so we take the highest and most destructive gear score, in this case it is fish traps with a score of 5, and assign that as the allowed maximum score for that zone. The blue zone only allows 1 gear type, and so it is automatically assigned that score, in this case 4. The green zone is a no take zone and so it is automatically assigned a score of 0 since no gears are allowed.

Banned Minimum Scores

The banned minimum score focuses on the lowest and least destructive gear score within each zone. In order to determine a zone score without knowing what gears are allowed, we needed to look at the banned gears and make a major assumption. The assumption is that if an MPA management team would go to certain lengths to ban a fishing gear with a low gear score, then we are assuming that all of the gears with a higher and more destructive score are also banned. The concept here is the same as for the allowed maximum score, but reversed. The lowest and least destructive gear score within the MPA

13 zone is the banned minimum score. If there is only one gear permitted in a zone, then the gear score of that gear is automatically the banned minimum score. For no take zones where no fishing is permitted, the banned minimum score is automatically 0 since no gear are allowed. Therefore, as with the allowed maximum score, the higher the zone score, the more destructive activities are permitted within the MPA zone. Figure 5 below provides an example of how the banned minimum score is calculated for different types of MPA zones.

Figure 5. This graphic provides an example of the banned minimum zone scoring for a zoned MPA. The purple zone bans 3 different gear types, and so we take the lowest and least destructive gear score, in this case it is dip nets with a score of 2, and assign that as banned minimum score for that zone. The blue zone only bans 1 gear type, and so it is automatically assigned that score, in this case 4. The green zone is a no take zone and so it is automatically assigned a score of 0 since all gears are banned.

Combined Scores

In order to determine if the banned minimum score was a suitable proxy for the allowed maximum score, we looked at the zone scores to see if there was a positive correlation. There were 95 MPAs that had both allowed and banned scores, excluding no take MPAs with scores of 0 that were removed. The results below (Chart 1) show that there is a positive correlation between the allowed maximum and banned minimum zone scores.

14 The positive correlation between the scores helps to support our assumption that serves as

the basis for the banned minimum scores – that if an MPA management team would go to

certain lengths to ban a fishing gear with a low gear score, then we are assuming that all of

the gears with a higher gear score are also banned. The allowed maximum and banned

minimum score summary statistics can be seen in Appendix, Table 3.

Correlation Between Allowed Maximum and Banned Minimum MPA Zone Scores

7

6 y = 0.4394x + 1.2439 5

4

3

2

1 Banned Minimum Zone Score 0 0 1 2 3 4 5 6 7 8 Allowed Maximum Zone Score

Chart 1. In this study, there are 95 MPAs with both allowed maximum and banned minimum zone scores. This chart plots the relationship between the allowed and banned zones scores for each MPA, showing a positive correlation.

Since there is a positive correlation between the allowed and banned zone scores,

the banned scores are a suitable proxy for the allowed scores. As a result, we created a

combined score where we used the banned score as a proxy for the allowed score for the

MPAs where no allowed score was available (Appendix, Table 4).

15 MPA Index Classifications

From the combined zone scores, the MPA index classification scores were calculated. The MPA index classification scores take the area of each zone relative to the entire MPA area into account to determine its impact on the overall MPA. As a result, larger

MPA zones and their regulations have more of an influence on the overall MPA index classification score since they affect a greater portion of the MPA. The MPA index classification scores were calculated using the equation from the Horta e Costa et al. paper

(Figure 6). The MPA scores range from 0 to 9, from fully protected to unprotected.

Figure 6. This equation from Horta e Costa et al. was used to determine the MPA index classification scores. Each zone score within an MPA is multiplied by the zone’s proportional area in the MPA and then summed to get the overall MPA score.

However, after reviewing the MPA index classification scores for each MPA, we noticed some of the scores were likely overestimated. There were a handful of small-scale

MPAs that only allow traditional or recreational fishing with scores of 7 or more. This may be due to many small-scale MPAs having general lists of allowed and banned fishing gear.

For example, ‘allowing nets’ instead of ‘allowing cast nets and drop nets’. The former includes destructive nets such as purse seining (bottom) and results in a score of 9, whereas the latter results only in a score of 3. There is uncertainty surrounding whether this accurately reflects the gear being used in the MPA or if this is a result of the destructive gear not being explicitly banned. In order to correct for this, the maximum MPA index classification score for this analysis was reduced to 7. Therefore, any MPA with a score of 7 or greater was given an MPA index classification score of 7.

16 Geospatial Analysis

The next step in the analysis is to assess the relationship between the MPA scores and ecological and socioeconomic data. The datasets listed previously in Table 1 are mostly global, country-level datasets in Excel or tabular format. However, the Dryad Marine

Biodiversity dataset was in raster format and the Reefs at Risk Revisited dataset was in vector format. The data for these layers was extracted using ArcGIS Pro and Arcpy.

The MPA polygon layer and marine biodiversity raster layer were input into ArcGIS

Pro. The marine biodiversity layer displays biodiversity on a scale from 0 to 1, low to high.

Feature to Point used to determine the central point of each MPA and create a point layer.

Extract Values to Points was used to extract the marine biodiversity value at the central point within each MPA. This data was then exported to Excel.

The Reefs at Risk Revisited vector dataset shows coral reef area divided by the level at which the reef is threatened by climate change and human impacts. The threat levels include: low, medium, high, and very high. Using Arcpy, the percentage of area within each reef that is highly threatened or very highly threatened was determined. This data was exported as a table using GeoPandas.

Statistical Analysis

One of the main objectives in this analysis was to examine the relationship between

MPA level of protection from fishing and contextual factors. In order to do so, 25 different country-specific datasets on ecological and socioeconomic conditions were compiled

(Table 1). The majority of this data was ranked; therefore, Spearman’s Rank Order

Correlation tests were conducted to determine correlations between MPA level of protection and each factor.

17 Results

Global MPA Index Classification Results

The summary statistics for the MPA index classification scores were calculated both

including and excluding no-take MPAs. When including the no-take MPAs, the scores

ranged from a minimum of 0 for the no-take MPAs to a maximum of 7 for the most

destructive MPAs. The average score globally was 3.10, with a median of 3.68 and a mode

of 0. When excluding the no-take MPAs, the scores ranged from a minimum of 1.08 to a

maximum of 7. The average score globally was 4.62, with a median of 4.00 and a mode of

4.00. These results can be seen in the histogram (Chart 2) and table (Table 3) below.

MPA Index ClassiXication Scores 45 40 35 30 25 20 Frequency 15 10 5 0 0 1 2 3 4 5 6 7 MPA Index ClassiXication Score

Chart 2. This histogram displays the distribution of MPA index classification scores globally.

Including No-Take MPAs Excluding No-Take MPAs Mean 3.10 4.62 Median 3.68 4.00 Mode 0.00 4.00 Minimum 0.00 1.08 Maximum 7.00 7.00 Table 3. This table displays the MPA index classification scores summary statistics.

18 Regional MPA Index Classification Results

The MPA index classification scores varied by region. The summary statistics for

each region can be seen in the table (Table 4) and map (Figure 7) below. When compared

to the global average score of 3.10, the Western Pacific had a lower score of 2.70. The

Caribbean and Northern Pacific regions had slightly higher averages when compared to the

global average, followed by the Indian Ocean and Mediterranean. The Northern Atlantic

had the highest average score of 6.39. However, a caveat is that our dataset may not be

representative of each region as a whole, so we cannot say that one region is better or

worse than another based on our dataset alone.

Indian Northern Northern Western Globally Caribbean Mediterranean Ocean Atlantic Pacific Pacific Mean 3.10 3.13 4.57 4.90 6.39 3.33 2.70 Median 3.68 3.68 5.47 4.90 6.39 3.46 2.00 Mode 0.00 4.00 NA NA NA 0.00 0.00 Min 0.00 0.00 0.00 4.00 6.39 0.00 0.00 Max 7.00 7.00 6.95 5.79 6.39 7.00 7.00 Table 4. This table displays the summary statistics for each marine region compared to the global statistics.

Figure 7. This map classifies the regional MPA index classification score averages from low (green) to high (red) in reference to Table 4. 19

In addition to variation of MPA index classification scores globally across regions, there is also variability within regions. Off the coast of Belize, the scores range from 0 to 7

(Figure 8). The same score distribution occurs off the southeast coast of Australia (Figure

9).

Figure 8. This map displays the variation of scores off the coast of Belize.

20

Figure 9. This map displays the variation of scores off the southeast coast of Australia.

Threatened Areas of Importance

MPAs are important tools for protecting marine biodiversity and coral reef areas.

The MPA index classification scores for MPAs containing higher than average biodiversity and highly threatened or very highly threatened coral reefs were examined. The summary

21 statistics for highly biodiverse MPAs and MPAs containing threatened reefs are compared

to the global average below (Table 5). Both MPAs with high biodiversity and threatened

coral reefs have a higher average score than the global average score.

Globally High Biodiversity Threatened Coral Reefs Mean 3.10 4.27 3.99 Median 3.68 5.00 3.68 Mode 0.00 0.00 NA Minimum 0.00 0.00 0.00 Maximum 7.00 7.00 7.00 Table 5. This table displays the summary statistics for highly biodiverse MPAs and MPAs containing threatened coral reefs compared to the global statistics.

Statistical Results

Spearman’s Rank Order Correlation tests were used to assess the relationships

between the MPA index classification scores and the 25 environmental and socioeconomic

datasets (Appendix, Figure 1). Of the 25 datasets, only two datasets showed any

statistically significant correlation with the MPA index classification scores at the five

percent level. Infant mortality had a weak positive relationship, meaning that in countries

with MPA scores that were higher or allowed more destructive activities, there was higher

infant mortality. Conversely, the corruption perception index had a weak negative

relationship, meaning MPA scores were lower and less destructive in countries with higher

perceived levels of corruption.

Discussion

Overall, the global average MPA index classification score is relatively low, as seen in

Chart 2 and Table 3. The average score is 3.10 when including no-take MPAs and 4.62 when

excluding no-take MPAs. As we look closer at these MPAs, there is variability across and

within regions. However, this is partially due to large clusters of MPAs in certain regions

22 and very few MPAs in other regions. Table 4 and the map in Figure 7 show the variability of

MPA index classification scores across marine regions. The Caribbean and Western Pacific regions contain 49 and 55 MPAs, respectively, and have the lowest regional scores. The

Caribbean’s average score is 3.13, only slightly higher than the global average. The Western

Pacific’s average score is 2.70, which is lower than the global average. The North Atlantic has the highest regional score of 6.39, however, this is not reflective of the entire region as there is only 1 MPA from that region in this analysis. The same is true for the

Mediterranean with the second highest score of 4.90. Only 2 MPAs from the Mediterranean were used in this analysis. Here it is encouraging to see regions with many MPAs generally have low average MPA index classification scores.

Looking even closer, we can see the MPA index classification score variability within regions such as off the coasts of Belize (Figure 8) and southeast Australia (Figure 9). The scores in the areas range from 0 or entirely no-take to 7 or allowing the most destructive gears. This indicates that there is a lack of country level regulations for MPAs, and that each individual MPA can implement and enforce its own regulations. This lack of consistency could prove to be an issue in protecting marine resources and biodiversity, particularly for small countries. Smaller countries have less variability of marine resources and biodiversity surrounding them. When small countries, especially small island countries with high biodiversity, do not set a baseline for MPA protection, this puts marine biodiversity and resources at an increased risk. Whereas in larger countries like Australia, this is less of a concern as marine biodiversity and resources vary depending on where you are located.

23 When looking at threatened marine areas of importance, particularly MPAs with higher than average levels of biodiversity and highly and very highly threatened coral reefs, there is some concern regarding their MPA index classification scores when compared to the global average. Both MPAs with high biodiversity and threatened coral reefs have MPA index classification scores higher than the global average of 3.10. High biodiversity MPAs have an average score of 4.27 and threatened coral reef MPAs have an average score of 3.99 when including no-take MPAs. While statistical tests will have to be done to see if this is significant, and these scores are generally low, it should be noted that MPAs in the more biodiverse areas of the ocean might be allowing more damaging fishing gear and are less well protected than others on average. This is especially important since many of these tropical regions will also continue to see damaging effects from climate change into the future.

As an example, American Samoa accounts for 13 of the 34 MPAs with high levels of biodiversity. In Figure 10, we can see that American Samoa is surrounded by high levels of biodiversity. There are variable MPA regulations throughout the country, with some MPAs prohibiting fishing entirely and some allowing moderate to very destructive types of fishing in these high biodiversity areas. This underscores the importance of assessing level of protection for MPAs in relation to other social and environmental factors. Looking at additional factors helps to better inform management strategies for protection and also helps to target areas of importance when creating MPAs.

24

Figure 10. This map shows the biodiversity surrounding American Samoa and the MPA index classification scores of MPAs off the coast of the country, which range from 0 to 7.

25 The statistical analysis allowed us to look further into the relationship between the

MPA index classification scores and our suite of environmental and socioeconomic factors.

Out of the 25 datasets used in this analysis, only two factors were significantly correlated with MPA index classification scores at the 5 percent level. Infant mortality had a weak positive correlation and perceived level of corruption had a weak negative correlation.

However, these relationships are likely spurious as there is no clear causal relationship between these variables. We anticipated there to be significant negative correlations with factors such as biodiversity, coastal environmental status, gross domestic product, and the human development index. However, the lack of any strong correlations could be due to a lack of data. First, there was a lack of consistent data reporting across MPAs used in this analysis. Second, we struggled to find higher resolution datasets on a more local level. As a result, we were forced to rely on country level data for many variables and country level data does not often correlate well with what is happening on a local scale surrounding each

MPA.

Conclusion

This study found that MPA fishing regulations vary greatly between locations. We were able to see variability globally across regions and also within regions. Generally, MPA level of protection is strong with low overall MPA index classification scores globally.

However, there are potential concerns for highly biodiverse and coral reef areas.

This study also revealed many data concerns surrounding MPAs. MPA data reporting is not consistent and regulations are not always accurate and reflective of what is actually going on in the MPA, which make its difficult to make comparisons across MPAs.

26 This study highlights the need for standardized reporting of MPA fishing regulations with streamlined data collection methods.

Additionally, there are very few local level datasets on environmental and socioeconomic conditions that have consistent global data, and even country level datasets are lacking for smaller countries. Local level data would paint a clearer and more accurate picture of the conditions surrounding the MPAs. We hope that this study can serve as a baseline for when local level and consistent data is more readily available in the future, and that it will assist in determining which MPAs are best protecting ocean resources and help to inform MPA regulations and management strategies.

27 Appendix

Fishing Gear Group Fishing Gear Gear Score Hand Capture Conching 3 Gleaning 3 Hand Harvesting 3 Hand Ropes 3 Intertidal Hand Captures 3 Lobstering/Crabbing 4 Line Hooks 3 Lines (Jigs, Hook and Line, Rod, Troll, Hand) 4 Rods 4 Surface Fishing 4 Drift Lines 5 Drop Lines 5 Set Lines 5 Wet Lining 5 Longlines (Bottom) 6 Longlines (Pelagic) 6 Spear Harpoon 3 Hawaiian Slings or Pole Spear 3 Gaff 3 SCUBA for Fishing/Collecting 4 Spearfishing/Diving (Free Diving) 4 Spearfishing/Diving (SCUBA) 4 Traps Basket Traps 5 Fish Traps 5 Pots 5 Traps (General) 5 Traps (Lobster/Octopus/Crab) 5 Fixed Fish Traps 'Madrague' 6 Small Bottom Net Hand Dredges (Bivalves) 5 Fixed Nets 6 Large Bottom Nets Drag Netting 7 Beach Seines 8

28 Trammel Nets 8 Purse Seining (Bottom) 9 Small Pelagic Nets Dip Nets (Scoop Nets/Land Nets) 2 Bait Fishing/Netting 3 Cast Nets (Throw Nets) 3 Drop Nets 3 Garfish Nets 3 Hand Nets (scoop Nets) 3 Pelagic Nets Pull Nets 6 Shark Nets 7 Large Pelagic Nets Frame Nets 5 Lift Nets 5 Surrounding Nets 5 Purse Seining (Pelagic) 6 Push Nets 6 Trawl (Pelagic) 6 Other Nets Crab Netting 4 Hoop Nets 4 Gill Nets 6 Mesh Nets 6 Nets 6 Set Nets 6 Tangle Nets 6 Wire Nets 6 Drift Nets 6 Haul Nets 7 Seine 7 Bottom Trawl Dredges (Bivalves) 7 Trawl (Bottom) 9 Aquarium Aquarium Collecting 7 Chemicals Bleaching Agents 9 Poisons, Noxious Chemicals 9 Electric Electric Charges 6

29 Explosives Firearms 6 Explosives 9 Table 1. This chart shows the fishing gear examined in this study and their assigned gear scores. The scores range from 1 to 9, with a low score being low impact and a high score being high impact.

Allowed Banned MPA ID MPA Country MPA Name MPA Type Maximum Minimum Gear Score Gear Score Bacalar Chico Marine Reserve and 5 Belize National Park MZMU 4.88 2.75 Caye Caulker Marine and Forest 7 Belize Reserve MZMU 1.96 1.31 Gladden Spit and Silk Cayes Marine 8 Belize Reserve MZMU 1.65 10 Belize Halfmoon Caye Natural Monument SZNT 0.00 0.00 11 Belize Hol Chan Marine Reserve MZMU 1.08 12 Belize Laughing Bird Caye National Park SZNT 0.00 0.00 13 Belize Port Honduras Marine Reserve MZMU 3.96 15 Belize South Water Caye Marine Reserve MZMU 3.25 40 Dominican Republic Jaragua National Park MZMU 3.23 42 Dominican Republic Montecristi National Park SZMU 6.00 6.00 54 Jamaica Ocho Rios Marine Park SZMU 7.00 73 Turks and Caicos Islands West Caicos Marine National Park SZMU 6.00 3.00 74 U.S. Virgin Islands Buck Island Reef National Monument SZNT 0.00 0.00 75 U.S. Virgin Islands Virgin Islands National Park SZMU 4.00 4.00 78 Bahamas Fowl Cays National Park SZNT 0.00 0.00 84 Bahamas South Berry Islands Marine Reserve SZNT 0.00 0.00 97 Bahamas Pelican Cays Land and Sea Park SZNT 0.00 0.00 109 United States Dry Tortugas National Park MZMU 2.02 1.52 Cayos Cochinos National Marine 124 Honduras Monument MZMU 4.04 126 Honduras Sandy Bay-West End Marine Reserve SZMU 4.00 2.00 Salt River Bay National Historical 150 SZNT 0.00 U.S. Virgin Islands Park and Ecological Preserve 0.00 Parque Nacional Marino Isla de 151 Panama Bastimentos MZMU 3.68 185 Belize Caye Bokel SZMU 4.00 2.00 South Point (Spawning Aggregation 186 SZNT 0.00 Belize Site Reserves) / 'El Nic' 0.00

30 Oostpunt 'East Point' Underwater 210 4.00 Curacao Park SZMU 4.00 West Bay Cemetery - Victoria House 213 2.00 Cayman Islands (Grand Cayman) SZMU 4.00 North West Point - West Bay 223 2.00 Cayman Islands Cemetery (Grand Cayman) SZMU 4.00 Mary's Bay - East Point (Little 226 2.00 Cayman Islands Cayman) SZMU 4.00 227 Cayman Islands South Hole Sound (Little Cayman) SZMU 4.00 2.00 Dick Sessingers Bay - Beach Point 229 2.00 Cayman Islands (Cayman Brac) SZMU 4.00 Bloody Bay - Jackson Point (Little 231 2.00 Cayman Islands Cayman) SZMU 4.00 Preston Bay - Main Channel MP 232 2.00 Cayman Islands (Little Cayman) SZMU 4.00 267 Mexico Banco Chinchorro MZMU 5.72 4.77 270 Mexico Arrecife de Puerto Morelos MZMU 3.11 272 Mexico Parque Nacional Arrecife de Cozumel MZMU 2.12 273 Mexico Arrecifes de Xcalak MZMU 3.07 Princess Alexandra Land and Sea 298 3.00 Turks and Caicos Islands National Park SZMU 6.00 303 Puerto Rico Canal Luis Pena SZNT 0.00 0.00 322 Cayman Islands Barkers Replenishment Zone SZMU 4.00 2.00 330 U.S. Virgin Islands St. Croix East End Marine Park MZMU 3.55 2.65 331 Cayman Islands George Town Marine Park SZMU 4.00 2.00 334 Cayman Islands Sandbar Wildlife Interaction Zone SZNT 0.00 0.00 Discovery Bay Special Fishery 338 SZNT 0.00 Jamaica Conservation Area 0.00 343 United States Key West National Wildlife Refuge MZMU 6.99 5.99 394 Australia Cape Howe Marine National Park SZNT 0.00 0.00 Parque Nacional Marino Golfo de 400 Panama Chiriqui MZMU 2.64 1.32 401 Australia Governor Island Marine Reserve SZNT 0.00 0.00 Hanauma Bay Marine Life 402 SZNT 0.00 United States Conservation District 0.00 Mnazi Bay-Ruvuma Estuary Marine 410 Tanzania Park MZMU 6.24 2.67 414 Australia Port Davey Marine Reserve MZMU 2.23 0.89 Port Phillip Heads Marine National 415 SZNT 0.00 Australia Park 0.00 Pupukea Marine Life Conservation 416 United States District MZMU 2.24

31 417 American Samoa Rose Atoll National Monument SZNT 0.00 0.00 426 Australia Aldinga Reef Sanctuary Zone SZNT 0.00 0.00 427 Seychelles Baie Ternay SZNT 0.00 0.00 428 Australia Batemans Marine Park MZMU 5.66 429 Australia Beware Reef Marine Sanctuary SZNT 0.00 0.00 430 Australia Bushranger's Bay Aquatic Reserve SZNT 0.00 0.00 431 Australia Cabbage Tree Bay Aquatic Reserve SZNT 0.00 0.00 432 Costa Rica Caletas-Ario Wildlife Refuge SZMU 7.00 6.00 433 Costa Rica Camaronal National Wildlife Refuge MZMU 5.68 Cape Rodney-Okakari Point Marine 435 SZNT 0.00 New Zealand Reserve 0.00 443 Australia Jervis Bay Marine Park MZMU 4.92 4.11 445 Australia Kent Group Marine Reserve MZMU 2.39 0.96 453 Australia Ninepin Point Marine Reserve SZNT 0.00 0.00 Ningaloo Commonwealth Marine 454 Australia Reserve MZMU 3.79 456 Australia Point Cooke Marine Sanctuary SZNT 0.00 0.00 457 New Zealand Poor Knights Islands Marine Reserve SZNT 0.00 0.00 458 Australia Port Noarlunga Aquatic Reserve MZMU 3.64 Port Stephens - Great Lakes Marine 459 Australia Park MZMU 5.75 4.10 461 Australia Ricketts Point Marine Sanctuary SZNT 0.00 0.00 462 Australia Shiprock Aquatic Reserve SZNT 0.00 0.00 466 New Zealand Te Matuku Marine Reserve SZNT 0.00 0.00 467 New Zealand Te Paepae o Aotea Marine Reserve SZNT 0.00 0.00 468 Australia Tinderbox Marine Reserve SZNT 0.00 0.00 Tuhua (Mayor Island) Marine 470 SZNT 0.00 New Zealand Reserve 0.00 472 Australia Bronte-Coogee Aquatic Reserve SZMU 5.00 474 Panama Coiba National Park MZMU 3.58 476 Spain Reserva Marina Isla del Toro SZMU 4.00 2.00 Reserva Marina del Levante de 477 Spain Mallorca - Cala Rajada MZMU 5.79 4.14 North Sydney Harbour Aquatic 479 4.00 Australia Reserve SZMU 4.00 481 Australia Shoalwater Islands Marine Park MZMU 6.39 4.53 Whanganuai A Hei (Cathedral Cove) 488 SZNT 0.00 New Zealand Marine Reserve 0.00 490 Guam Piti Bomb Holes SZMU 7.00 2.00 492 United States Kealakekua Bay MZMU 3.04 Reserva Marina de La Restinga - Mar 586 Spain de las Calmas MZMU 6.39

32 594 United States Honolua SZNT 0.00 0.00 596 United States Lapakahi MZMU 3.88 597 United States Molokini MZMU 2.18 598 United States Old Kona Airport SZMU 4.00 5.00 599 United States Waialea SZMU 7.00 6.00 Virgin Islands Coral Reef National 600 U.S. Virgin Islands Monument SZMU 3.00 623 American Samoa Vatia Village Marine Protected Area SZNT 0.00 0.00 641 Guam Achang Reef Flat Marine Preserve SZMU 7.00 2.00 650 Guam Guam National Wildlife Refuge SZMU 7.00 2.00 651 Guam Haputo Ecological Reserve Area SZNT 0.00 0.00 652 Guam Pati Point SZMU 7.00 2.00 653 Guam Tumon Bay SZMU 7.00 2.00 War in the Pacific National Historical 654 3.00 Guam Park SZMU 7.00 656 American Samoa Alofau Village Marine Protected Area SZMU 6.00 5.00 Amaua & Auto Village Marine 658 5.00 American Samoa Protected Area SZMU 7.00 659 American Samoa Aua Village Marine Protected Area SZMU 7.00 Fagamalo Village Marine Protected 660 SZNT 0.00 American Samoa Area 0.00 661 American Samoa Leone Pala SZMU 5.00 Masausi Village Marine Protected 662 5.00 American Samoa Area SZMU Matu'u & Faganeanea Village Marine 663 5.00 American Samoa Protected Area SZMU National Marine Sanctuary of 664 American Samoa American Samoa MZMU 5.00 665 American Samoa National Park of American Samoa SZMU 5.00 666 American Samoa Poloa Village Marine Protected Area SZMU 5.00 Sa'ilele Village Marine Protected 667 SZNT 0.00 American Samoa Area 0.00 Kona Coast Fishery Management 669 6.00 United States Area SZMU 7.00 West Hawaii Regional Fishery 670 4.00 United States Management Area SZMU Abrolhos Islands' Fish Habitat 671 Australia Protection Area MZMU 6.95 680 American Samoa Rose Atoll Wildlife Refuge SZNT 0.00 0.00 Muiron Islands Marine Management 681 Australia Area MZMU 6.50 742 Mozambique Quirimbas National Park MZMU 4.69

33 894 Indonesia Wayag SZNT 0.00 0.00 954 Australia Great Sandy Marine Park MZMU 6.36 4.44 955 Australia Casuarina Coastal Reserve SZMU 2.00 973 Australia Point Hicks Marine National Park SZNT 0.00 0.00 Cottesloe Reef Fish Habitat 976 2.00 Australia Protection Area SZMU 979 Australia Moreton Bay Marine Park MZMU 5.75 3.98 1014 Australia Booderee National Park MZMU 3.90 2.93 1016 American Samoa Ofu Vaoto Marine Park SZMU 5.00 1017 Solomon Islands NusaTupe SZNT 0.00 0.00 Table 2. This chart shows the allowed maximum and banned minimum MPA scores for each MPA. For both the allowed maximum score and the banned minimum score, the higher the score, the more damaging gear is allowed within the MPA. Therefore, in both cases, MPAs with lower scores offer greater protection. The chart also includes the MPA ID number, country, MPA name, and MPA type. The MPA types are: single zone no-take (SZNT), single zone multiple use (SZMU), and multiple zone multiple use (MZMU).

Including No-Take MPAs Excluding No-Take MPAs Allowed Maximum Banned Minimum Allowed Maximum Banned Minimum Mean 3.00 2.01 4.83 3.30 Median 3.61 2.00 4.00 3.00 Mode 0.00 0.00 4.00 2.00 Minimum 0.00 0.00 1.96 0.89 Maximum 7.00 6.00 7.00 6.00 Table 3. This chart shows the summary statistics for the allowed maximum and banned minimum scores.

MPA ID MPA Country MPA Name MPA Type Combined Score Bacalar Chico Marine Reserve and 5 Belize National Park MZMU 4.88 Caye Caulker Marine and Forest 7 Belize Reserve MZMU 1.96 Gladden Spit and Silk Cayes Marine 8 Belize Reserve MZMU 1.65 10 Belize Halfmoon Caye Natural Monument SZNT 0.00 11 Belize Hol Chan Marine Reserve MZMU 1.08 12 Belize Laughing Bird Caye National Park SZNT 0.00 13 Belize Port Honduras Marine Reserve MZMU 3.96 15 Belize South Water Caye Marine Reserve MZMU 3.25 40 Dominican Republic Jaragua National Park MZMU 3.23 42 Dominican Republic Montecristi National Park SZMU 6.00

34 54 Jamaica Ocho Rios Marine Park SZMU 7.00 73 Turks and Caicos Islands West Caicos Marine National Park SZMU 6.00 74 U.S. Virgin Islands Buck Island Reef National Monument SZNT 0.00 75 U.S. Virgin Islands Virgin Islands National Park SZMU 4.00 78 Bahamas Fowl Cays National Park SZNT 0.00 84 Bahamas South Berry Islands Marine Reserve SZNT 0.00 97 Bahamas Pelican Cays Land and Sea Park SZNT 0.00 109 United States Dry Tortugas National Park MZMU 2.02 Cayos Cochinos National Marine 124 Honduras Monument MZMU 4.04 126 Honduras Sandy Bay-West End Marine Reserve SZMU 4.00 Salt River Bay National Historical 150 SZNT U.S. Virgin Islands Park and Ecological Preserve 0.00 Parque Nacional Marino Isla de 151 Panama Bastimentos MZMU 3.68 185 Belize Caye Bokel SZMU 4.00 South Point (Spawning Aggregation 186 SZNT Belize Site Reserves) / 'El Nic' 0.00 Oostpunt 'East Point' Underwater 210 Curacao Park SZMU 4.00 West Bay Cemetery - Victoria House 213 Cayman Islands (Grand Cayman) SZMU 4.00 North West Point - West Bay 223 Cayman Islands Cemetery (Grand Cayman) SZMU 4.00 Mary's Bay - East Point (Little 226 Cayman Islands Cayman) SZMU 4.00 227 Cayman Islands South Hole Sound (Little Cayman) SZMU 4.00 Dick Sessingers Bay - Beach Point 229 Cayman Islands (Cayman Brac) SZMU 4.00 Bloody Bay - Jackson Point (Little 231 Cayman Islands Cayman) SZMU 4.00 Preston Bay - Main Channel MP 232 Cayman Islands (Little Cayman) SZMU 4.00 267 Mexico Banco Chinchorro MZMU 5.72 270 Mexico Arrecife de Puerto Morelos MZMU 3.11 272 Mexico Parque Nacional Arrecife de Cozumel MZMU 2.12 273 Mexico Arrecifes de Xcalak MZMU 3.07 Princess Alexandra Land and Sea 298 Turks and Caicos Islands National Park SZMU 6.00 303 Puerto Rico Canal Luis Pena SZNT 0.00 322 Cayman Islands Barkers Replenishment Zone SZMU 4.00 330 U.S. Virgin Islands St. Croix East End Marine Park MZMU 3.55

35 331 Cayman Islands George Town Marine Park SZMU 4.00 334 Cayman Islands Sandbar Wildlife Interaction Zone SZNT 0.00 Discovery Bay Special Fishery 338 SZNT Jamaica Conservation Area 0.00 343 United States Key West National Wildlife Refuge MZMU 6.99 394 Australia Cape Howe Marine National Park SZNT 0.00 Parque Nacional Marino Golfo de 400 Panama Chiriqui MZMU 2.64 401 Australia Governor Island Marine Reserve SZNT 0.00 Hanauma Bay Marine Life 402 SZNT United States Conservation District 0.00 Mnazi Bay-Ruvuma Estuary Marine 410 Tanzania Park MZMU 6.24 414 Australia Port Davey Marine Reserve MZMU 2.23 Port Phillip Heads Marine National 415 SZNT Australia Park 0.00 Pupukea Marine Life Conservation 416 United States District MZMU 2.24 417 American Samoa Rose Atoll National Monument SZNT 0.00 426 Australia Aldinga Reef Sanctuary Zone SZNT 0.00 427 Seychelles Baie Ternay SZNT 0.00 428 Australia Batemans Marine Park MZMU 5.66 429 Australia Beware Reef Marine Sanctuary SZNT 0.00 430 Australia Bushranger's Bay Aquatic Reserve SZNT 0.00 431 Australia Cabbage Tree Bay Aquatic Reserve SZNT 0.00 432 Costa Rica Caletas-Ario Wildlife Refuge SZMU 7.00 433 Costa Rica Camaronal National Wildlife Refuge MZMU 5.68 Cape Rodney-Okakari Point Marine 435 SZNT New Zealand Reserve 0.00 443 Australia Jervis Bay Marine Park MZMU 4.92 445 Australia Kent Group Marine Reserve MZMU 2.39 453 Australia Ninepin Point Marine Reserve SZNT 0.00 Ningaloo Commonwealth Marine 454 Australia Reserve MZMU 3.79 456 Australia Point Cooke Marine Sanctuary SZNT 0.00 457 New Zealand Poor Knights Islands Marine Reserve SZNT 0.00 458 Australia Port Noarlunga Aquatic Reserve MZMU 3.64 Port Stephens - Great Lakes Marine 459 Australia Park MZMU 5.75 461 Australia Ricketts Point Marine Sanctuary SZNT 0.00 462 Australia Shiprock Aquatic Reserve SZNT 0.00 466 New Zealand Te Matuku Marine Reserve SZNT 0.00

36 467 New Zealand Te Paepae o Aotea Marine Reserve SZNT 0.00 468 Australia Tinderbox Marine Reserve SZNT 0.00 Tuhua (Mayor Island) Marine 470 SZNT New Zealand Reserve 0.00 472 Australia Bronte-Coogee Aquatic Reserve SZMU 5.00 474 Panama Coiba National Park MZMU 3.58 476 Spain Reserva Marina Isla del Toro SZMU 4.00 Reserva Marina del Levante de 477 Spain Mallorca - Cala Rajada MZMU 5.79 North Sydney Harbour Aquatic 479 Australia Reserve SZMU 4.00 481 Australia Shoalwater Islands Marine Park MZMU 6.39 Whanganuai A Hei (Cathedral Cove) 488 SZNT New Zealand Marine Reserve 0.00 490 Guam Piti Bomb Holes SZMU 7.00 492 United States Kealakekua Bay MZMU 3.04 Reserva Marina de La Restinga - Mar 586 Spain de las Calmas MZMU 6.39 594 United States Honolua SZNT 0.00 596 United States Lapakahi MZMU 3.88 597 United States Molokini MZMU 2.18 598 United States Old Kona Airport SZMU 4.00 599 United States Waialea SZMU 7.00 Virgin Islands Coral Reef National 600 U.S. Virgin Islands Monument SZMU 3.00 623 American Samoa Vatia Village Marine Protected Area SZNT 0.00 641 Guam Achang Reef Flat Marine Preserve SZMU 7.00 650 Guam Guam National Wildlife Refuge SZMU 7.00 651 Guam Haputo Ecological Reserve Area SZNT 0.00 652 Guam Pati Point SZMU 7.00 653 Guam Tumon Bay SZMU 7.00 War in the Pacific National Historical 654 Guam Park SZMU 7.00 656 American Samoa Alofau Village Marine Protected Area SZMU 6.00 Amaua & Auto Village Marine 658 American Samoa Protected Area SZMU 7.00 659 American Samoa Aua Village Marine Protected Area SZMU 7.00 Fagamalo Village Marine Protected 660 SZNT American Samoa Area 0.00 661 American Samoa Leone Pala SZMU 5.00 Masausi Village Marine Protected 662 5.00 American Samoa Area SZMU

37 Matu'u & Faganeanea Village Marine 663 5.00 American Samoa Protected Area SZMU National Marine Sanctuary of 664 American Samoa American Samoa MZMU 5.00 665 American Samoa National Park of American Samoa SZMU 5.00 666 American Samoa Poloa Village Marine Protected Area SZMU 5.00 Sa'ilele Village Marine Protected 667 SZNT American Samoa Area 0.00 Kona Coast Fishery Management 669 United States Area SZMU 7.00 West Hawaii Regional Fishery 670 4.00 United States Management Area SZMU Abrolhos Islands' Fish Habitat 671 Australia Protection Area MZMU 6.95 680 American Samoa Rose Atoll Wildlife Refuge SZNT 0.00 Muiron Islands Marine Management 681 Australia Area MZMU 6.50 742 Mozambique Quirimbas National Park MZMU 4.69 894 Indonesia Wayag SZNT 0.00 954 Australia Great Sandy Marine Park MZMU 6.36 955 Australia Casuarina Coastal Reserve SZMU 2.00 973 Australia Point Hicks Marine National Park SZNT 0.00 Cottesloe Reef Fish Habitat 976 2.00 Australia Protection Area SZMU 979 Australia Moreton Bay Marine Park MZMU 5.75 1014 Australia Booderee National Park MZMU 3.90 1016 American Samoa Ofu Vaoto Marine Park SZMU 5.00 1017 Solomon Islands NusaTupe SZNT 0.00 Table 4. This chart shows the combined MPA scores. This score is the allowed maximum score for each MPA where available, and where not available, the banned minimum score for the MPA. The chart also includes the MPA ID number, country, MPA name, and MPA type. The MPA types are: single zone no-take (SZNT), single zone multiple use (SZMU), and multiple zone multiple use (MZMU).

38

Figure 1. This chart shows the correlation matrix for the combined MPA index classification scores and 25 environmental and socioeconomic variables.

39 References

Aswani, S. and Furusawa, T. (2007) Do Marine Protected Areas Affect Human Nutrition and Health? A Comparison between Villages in Roviana, Solomon Islands. Coastal Management, 35(5), 545-565. https://doi.org/10.1080/08920750701593394

Campbell, S. J., Edgar, G. J., Stuart-Smith, R. D., Soler, G., and Bates, A. E. (2017). Fishing-gear restrictions and biomass gains for coral reef fishes in marine protected areas. Conservation Biology, 32(2). https://doi.org/10.1111/cobi.12996

Edgar, G. J., Stuart-Smith, R. D., Willis, T. J., Kininmonth, S., Baker, S. C., Banks, S., Barrett, N. S., Becerro, M. A., Bernard, A. T. F., Berkhout, J., Buxton, C. D., Campbell, S. J., Cooper, A. T., Davey, M., Edgar, S. C., Forsterra, G., Galvan, D. E., Irigoyen, A. J., Kushner, D. J., Moura, R., Parnell, P. E., Shears, N. T., Soler, G., Strain, E. M. A., and Thomson, R. J. (2014). Global conservation outcomes depend on marine protected areas with five key features. Nature, 506, 216–220. https://doi.org/10.1038/nature13022

Horta e Costa, B., Claudet, J., Franco, G., Erzini, K., Caro, A., and Gonçalves, E. J. (2016). A regulation-based classification system for Marine Protected Areas (MPAs). Elsevier Marine Policy, 72, 192-198. http://dx.doi.org/10.1016/j.marpol.2016.06.021

Lester, S. E. and Halpern, B. S. (2008). Biological responses in marine no-take reserves versus partially protected areas. Inter-Research, 367, 49-56. https://doi.org/10.3354/meps07599

Wenzel, L. and D’Lorio, M. (2011). Definition and Classification System for U.S. Marine Protected Areas. NOAA. https://nmsmarineprotectedareas.blob.core.windows.net/ marineprotectedareas-prod/media/archive/pdf/helpfulresources/factsheets/mpa_ classification_may2011.pdf

Selig, E. R., Kleisner, K. M., Ahoobim, O., Arocha, F., Cruz-Trinidad, A., Fujita, R., Hara, M., Katz, L., McConney, P., Ratner, B. D., Saavedra-Díaz, L. M., Schwarz, A., Thiao, D., Torell, E., Troeng, S., and Villasante, S. (2017). A typology of fisheries management tools: using experience to catalyse greater success. Fish and Fisheries, 18, 543-570. https://doi.org/10.1111/faf.12192

Selig, E. R., Hole, D. G., Allison, E. H., Arkema, K. K., McKinnon, M. C., Chu, J., Sherbinin, A., Fisher, B., Glew, L., Holland, M. B., Ingram, J. C., Rao, N. S., Russell, R. B., Srebotnjak, T., Teh, L. C. L., Troeng, S., Turner, W. R., and Zvoleff, A. (2018). Mapping global human dependence on marine ecosystems. Conservation Letters, e12617. https://doi.org/10.1111/conl.12617

Zupan, M., Fragkopoulou, E., Claudet, J., Erzini, K., Horta e Costa, B., and Gonçalves, E.J. (2018). Marine partially protected areas: drivers of ecological effectiveness. The Ecological Society of America, 16(7), 381-387. https://doi.org/10.1002/fee.1934

40