Understanding regulatory frameworks for large marine protected areas: Permits of the Great Barrier Reef Marine Park

Biological Conservation 237 (2019) 3–11

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Understanding regulatory frameworks for large marine protected areas: Permits of the Great Barrier Reef Marine Park

T

Graeme S. Cumminga, , Kirstin A. Dobbsb ⁎

a b

ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland 4811, Australia Great Barrier Reef Marine Park Authority, PO Box 1379, Townsville, Qld 4810, Australia

ABSTRACT

Increasing numbers of large marine protected areas (LMPAs) are being added to the global conservation estate, raising new challenges for marine social-ecological management and biodiversity conservation. To better understand the importance of spatial heterogeneity and scale in managing LMPAs, we undertook a quantitative, spatially explicit analysis of permit data from the Great Barrier Reef Marine Park. We geo-registered 10,030 permissions from 7478 permits for the period 2007–2017, extracted the information into a 2 × 2 km grid, aggregated the data into six different permission types and explored spatial patterns by permission type and numbers. Permission numbers of different types were all strongly and significantly correlated; access and transport permissions were the most numerous. Commercial harvesting permission numbers were negatively correlated with those for research and education, but not for tourism. Apart from research permissions, the influence of the immediate biophysical environment (coral reefs, proximity to shore) at this scale was low; permission numbers were more influenced by proximity to towns and population density. There was also a broad-scale latitudinal effect, with higher permission numbers in the south, independent of the human geography variables that we measured. Permit numbers have been increasing exponentially over the last decade and show no sign of declining. More generally, our analysis shows how permit data can inform the management activities and needs of LMPAs, while potentially providing a window into long-term shifts in user demands and changing management needs for conservation.

1. Introduction Recent years have seen increasing recognition that the oceans of the world are under threat from a range of anthropogenic pressures (Halpern et al., 2008; Gattuso et al., 2018). Dominant human influences on marine ecosystems include climate change, overfishing, and pollution, as well as a range of more localised impacts resulting from such activities as tourism, construction, shipping, and mining (Hughes et al., 2017a; Bellwood et al., in press). One of the primary conservation responses to these pressures has been the creation of Large Marine Protected Areas (LMPAs, also called Large Scale MPAs or LSMPAs) in which potentially harmful activities are either restricted or forbidden (Wilhelm et al., 2014; Ban et al., 2017; Sala et al., 2018). The vast majority of scientific effort in quantifying and understanding change within protected areas has historically focused on measuring and monitoring change in ecosystems, including both ecological communities and the abiotic environment (Partelow et al., 2018). However, protected areas are social-ecological systems (Cumming, 2016), and the assumption that managers control ecosystems becomes increasingly untenable at broader scales, where their ability to respond to environmental change through ecosystem protection or restoration is increasingly limited by practicalities (e.g., the costs of enforcement or out-planting aquarium-grown coral) and politics (Walters, 1997; ⁎

Balmford et al., 2004; Ban et al., 2017; Gill et al., 2017). Ultimately, managing a large marine protected area is often more about managing people and their impacts than about directly influencing populations or communities of organisms (Cumming et al., 2015; Cumming, 2016; Christie et al., 2017). With the possible exception of research on fisheries management and compliance (Ban et al., 2017), little has been published about spatial heterogeneity in human activities in LMPAs. This is important because a growing body of research shows that at broad spatial extents, where habitat heterogeneity is higher, it is often both costly and problematic to attempt to implement a ‘one-size-fits all’ approach to management (Cumming et al., 2006; Mills et al., 2010; Johnson et al., 2012). LMPAs are a relatively new phenomenon. Prior to the year 2000 there were only six; the oldest of these is the Great Barrier Reef Marine Park (henceforth, ‘GBR’), which was established under the Commonwealth of Australia's Great Barrier Reef Marine Park Act 1975. By 2016 there were 21 established areas and at least four more ‘under development’ (Gruby et al., 2016), and by 2018 the number of established and promised LMPAs was up to 35 (O'Leary et al., 2018). Research suggests that larger MPAs conserve species more effectively (Edgar et al., 2014). However, for the new LMPAs in particular, the challenges associated with managing human use of a much larger marine area are poorly understood. Experiences from the management of large

Corresponding author. E-mail address: [email protected] (G.S. Cumming).

https://doi.org/10.1016/j.biocon.2019.06.007 Received 28 November 2018; Received in revised form 5 June 2019; Accepted 6 June 2019 Available online 18 June 2019 0006-3207/ Crown Copyright © 2019 Published by Elsevier Ltd. All rights reserved.

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G.S. Cumming and K.A. Dobbs

terrestrial protected areas suggest that management approaches that are scaled up directly from smaller areas, such as localised fire management, direct invasive species control, or intensive anti-poaching strategies, may not be effective at broader scales (Du Toit et al., 2003). Similar concerns have been voiced for LMPAs (Aswani and Hamilton, 2004; Wilhelm et al., 2014), making the management of LMPAs a potentially informative frontier for social-ecological research on scale and management. One obvious difference between small and large MPAs arises in the range of activities that occur within them. Most LMPAs include a wider range of habitats, users, and extractive activities than smaller MPAs; and LMPAs require extensive infrastructure to facilitate a diversity of access and conservation-related activities, such as education, law enforcement, and environmental monitoring. This diversity presents a challenge for both management and governance of LMPAs, and implies a need for strong as well as flexible legal and institutional frameworks (Garmestani and Allen, 2014). The relative extents and intensities of the different kinds of rules that are involved in LMPA operations are largely un-documented, however, raising practical challenges for actors who seek to develop or improve management regimes for LMPAs and analytical challenges for those seeking to understand the role of institutions in the management of LMPAs. Although there has been some previous research on permit systems relating to protected areas, this work has mostly focused on implementation and effectiveness (Brody et al., 2008; Pertierra and Hughes, 2013); we are unaware of previous spatially explicit analyses of permit distributions in protected areas. In this article we address this gap by using permit data from the GBR to (1) provide a first detailed case study of the kinds and frequencies of permits, and their distribution in space, within an LMPA; and (2) explore the influence of environmental context on the locations of permit applications. Our analysis is intended to both provide a context for further exploration of the role of permits and permitting in the management of LMPAs and present a data set that can potentially help managers to identify and analyse future stakeholder responses to environmental perturbations (e.g., cyclones, coral bleaching). The Great Barrier Reef Marine Park Zoning Plan 2003 establishes which types of activities require the permission of the Great Barrier Reef Marine Park Authority (GBRMPA) to use or enter the Marine Park. They include commercial tourism, research, and most facilities, such as pontoons, moorings, jetties, and non-tourist aircraft or vessel charter. Activities that do not require permission include low impact recreational use; most fishing activities, such as trawling, line fishing and large mesh gill netting, so long as they are conducted in accordance with Queensland Fisheries Act requirements; and shipping, so long as it is within the Designated Shipping Area. For > 30 years, the Authority has operated a joint permitting system with the Queensland Parks and Wildlife Service for the adjacent Great Barrier Reef (Coast) Marine Park (Day and Dobbs, 2013). Permit data offer a spatially explicit expression of a sub-set of institutions and rules in use (Ostrom, 1990). McGinnis (2011) states that rules in use describe “all relevant aspects of the institutional context within which an action situation is located”. He identified three different kinds of rules-in-use: formal rules (also termed rules-on-paper); a repertoire of strategies (including strategies, norms, and rules used on a daily basis); and property rights, which range from rights to access a location, through extractive rights, to full rights to buy and sell. Permit data can provide information across all three of these categories, whether directly or indirectly. For example: (1) permits are formal rules that are issued in accordance with other formal rules (e.g., legal permissions to undertake particular activities in particular locations, as summarised by the map of different use zones for the GBR); (2) the frequencies of applications for different activities provide insights into the intentions of participants to undertake different activities, and hence (assuming, reasonably, that there is at least some correlation between intention and action) into strategies and norms; and (3) the permitting process takes account of tenure by considering and including different rules for federal, state, community

(e.g. recreational) and individual (e.g., aboriginal) ownership. While not directly expressing the actual use actions of permitees, permits thus offer valuable insights into the nature and frequency of rules-in-use in the GBR and the intentions of LMPA users. Permits are an important management tool for both regulating the use of an LMPA and responding to user needs. According to Alder (1993), the permit system of the GBR has at least eight important roles in management. These include (1) fine-tuning the management of sites and activities, for example by preventing the loss of values associated with solitude; (2) regulating activities, such as tourism, research, and some commercial fishing activities; (3) implementing management plans, for example in managing threatened populations or facilitating reef recovery; (4) implementing strategies for resource allocation, for example when placing boat moorings or other infrastructure; (5) effecting policy, for example in reducing risks from invasive species or oil tankers; (6) collecting data on use of resources, such as numbers of operators using a given site for tourism; (7) monitoring impacts, for example through changes and extensions of permit requests; and (8) providing a focus for liaison with users of the Marine Park. Alder (1993) further points out that in cases where a ‘fast, reactive, site- or activity-specific management response’ is necessary, permits provide a faster and more scale-appropriate response than making changes to zoning plans or regulations that have to be approved by the Commonwealth Parliament. We used permit data for the GBR from a nearly 10-year period (2007 to mid-2017) to explore the spatial and temporal patterns of issued permits and the relationships between different kinds of permit. Our analysis suggests that in addition to the eight management contributions identified by Alder (1993), permit data can offer insights into the range and potential growth or decline of activities that require regulation. Analyses of permit data at regular intervals can facilitate the development of forward-looking, pro-active strategies for management within the GBR and other LMPAs. 2. Methods The permit data were obtained from the database maintained by the GBRMPA. The data set contained 7478 permits that provided 10,351 individual permissions that were valid between 2007 and mid-2017. Some permits were issued before 2007 and were captured in the new digital database created in 2007. Each individual record contained information about the operation and location for which activities were requested. There may be more than one permission on each permit document granted by the Authority. For example, many tourism related permits contain the following permissions: conduct of a tourism program, the installation, operation and maintenance of a facility such as a pontoon and the conduct of a vessel or aircraft charter operation. In our database, and for the subsequent analysis and discussion, each of these permissions is treated separately due to differences in their scale and focus. Permits are not issued using any kind of default setting, and each individual permission must be requested individually; co-occurring ‘bundles’ of different permission types thus describe genuine trends within the data rather than spurious correlations. Similarly, users must request and justify permit durations and there is no default time period for permit validity. We assembled spatial data layers (shapefiles; Table 1) for all locations mentioned in the permit data, reprojected all data into an Australian Equal-Areas Albers projection, and manually captured the shapefile identity and the identifier of the polygon for each individual permission. A total of 321 permissions could not be located reliably and were excluded from the analysis, leaving a sample size of 10,030 permissions. Permissions covered a wide range of different activities. We initially aggregated activities into 45 different permit classes, later merging these into six broader classes that captured the range of activities undertaken in the GBR for which permits are required. Details of the full 4

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G.S. Cumming and K.A. Dobbs

Table 1 The different shapefiles that were required to describe the locations of permits in the database. Great Barrier Reef (GBR) Marine Park zoning data is available at Geoportal Digital Data Download site http://www.gbrmpa.gov.au/geoportal/catalog/download/download.page. GBR Coast Marine Park zoning data is available at Queensland Spatial Catalogue at http://qldspatial.information.qld.gov.au/catalogue/. Original shapefile name

Source

Description

Great_Barrier_Reef_Marine_Park_Zoning Great_Barrier_Reef_Marine_Park_Boundary Plans_of_Management_boundaries__ALL_

GBRMPA GBRMPA GBRMPA

Special_Management_Areas Management_Areas_of_the_GBRMP__Poly_

GBRMPA GBRMPA

Cruise_Ship_Transit_Lanes_of_the_GBRMP Whale_Protection_Area Designated_Shipping_Areas_of_the_GBRMP HPOM_Settings_boundary WPOM_Settings_boundary WPOM_Langford_Black_Islands_Area WPOM_Water_Sports_Allowed CPOM_Reef_Anchorages CPOM_Locations CPOM_Sensitive_Locations Great_Barrier_Reef_Coast_Marine_Park_zoning

GBRMPA GBRMPA GBRMPA GBRMPA GBRMPA GBRMPA GBRMPA GBRMPA GBRMPA GBRMPA Queensland Government 2018

GBRCoastMarineParkOutline

QLD Parks/Queensland Government 2018 Department of Agriculture & Fisheries, QLD Government

Use zones of the GBRMP. Boundary of the Marine Park. Boundary of the areas included in Plans of Management for Cairns, Hinchinbrook, and the Whitsundays. Culturally and ecologically sensitive areas, some with restricted access. Four broad management areas of the GBRMP: (1) Far Northern Management Area; (2) Cairns/Cooktown Management Area; (3) Townsville/Whitsunday Management Area; (4) Mackay/Capricorn Management Area. Areas of active cruise ship traffic. Identified sensitive whale habitat. Areas of traffic for commercial ships (e.g. tankers). Use settings of Hinchinbrook Plan of Management. Use settings of Whitsundays Plan of Management. Prohibited fishing and collecting within Whitsundays as part of ongoing tourism program. Permitted areas within Whitsundays for motorized water sports activities. Permitted areas within Cairns for cruise ship anchorages. Use settings of Cairns Plan of Management. Culturally and ecologically sensitive areas with limited access within Cairns. Use zones of the Great Barrier Reef (Coast) Marine Park, a complementary zoning plan to the GBR. Boundary along the coast of Great Barrier Reef (Coast) Marine Park

QLD_Fisheries_Symbols

Permitted ornamental fishing and collecting areas in accordance with issued commercial fisheries licences. This composite data set contained overlapping polygons and was used to make separate data layers for marine fisheries zones, ornamental fishes, and lobster fisheries.

45-class classification and how each class was aggregated into one of six broader classes are provided in Appendix 1. The six permission classes used in our analysis were (1) commercial resource extraction (e.g., harvest fishing for lobster and sea cucumber, coral collection, aquarium trade), (2) education or research (e.g., scientific research, educational tours), (3) non-extractive tourism and special events (e.g., commercial snorkelling and diving tourism, watersports, fireworks shows, beach hire), (4) access and transport (e.g., cargo barges, boat hire, aeroplane landing), (5) built infrastructure (e.g., moorings, marker buoys, power cables, pontoons, and other facilities), and (6) pest removal (e.g. Acanthaster sp. crown of thorns starfish, Drupella sp. snails). Once each permission had been referenced to its corresponding polygon, we created a 2 × 2 km vector grid (‘fishnet’) covering the full extent of the GBR and extracted the unique identifier of each polygon into it, using intersect and spatial join commands in ArcGIS. The 2 × 2 km grid and individual shapefiles were then linked, using the merge command in R and the unique identifiers of each shapefile and polygon, to capture the number of permissions of each type in each grid cell (henceforth, termed the ‘permit grid’). We set the maximum spatial extent of the analysis as the outer boundary of the GBR Marine Park. We are unaware of any previous analyses that have treated permit data in this way, but the methods are standard approaches that are frequently applied to other data sources in environmental planning (McLain et al., 2013) and conservation planning (e.g., Ball and Possingham, 2000; Geselbracht et al., 2009). The time period of validity for each permit (in this case, not permission) was quantified based on its stated duration. Each year for which a permit was valid was scored

as a ‘1’, and other years as ‘0’. We summed columns of data by year and by permit to describe trends in permitting over the time frame of our study. We used the permit grid to visualize and compare spatial patterns in the numbers and kinds of different permit types. All statistical analyses were undertaken in R. All spatial analyses of permit numbers included each permission once only (i.e., permit totals by grid cell were calculated as the sum of all unique permissions within the nearly ten-year period of analysis, not as the number of years for which permits were valid). The first steps in the analysis were descriptive, focusing on describing the data and the relative numbers and locations of permits. We used a Spearman's correlation test (Sokal and Rohlf, 1981) on the numbers of each kind of permission in each grid cell within the period of analysis to test for spatial relationships between the patterns of different kinds of permit; and ran a principal components analysis (Dunteman, 1989) on the six columns of data (i.e., sums of each different permit type) associated with each grid cell to explore the major influences within the permit data set. We did not correct for spatial autocorrelation in these analyses because for our analyses, the spatial structure of the data set was the quantity of interest, not a nuisance variable (for further clarification of this distinction, see Legendre, 1993). We then asked how permission numbers in different categories were affected by their proximity to coastlines, coral reefs, and numbers of people living in the nearest coastal area. The attribute data were captured in a series of existing spatial data layers: a coastline map, the map of reef and island features from GBRMPA, and a point map of inhabited

Table 2 Ancillary data used in the analysis. All of these processing steps were undertaken in ESRI's ArcGIS software. Data set

Source

Processing

Coastline Coral Reefs Human settlement

GBRMPA GBR Marine Park Boundary GBRMPA GBR Features data set Natural Earth Database: Populated Places version 4.0.1. https://www.naturalearthdata. com/downloads/10m-cultural-vectors/10m-populated-places/ (checked 5-11-18). Used coordinates of grid cell centroids as calculated from our 2 × 2 km permit grid.

Used near command to calculate distance to coastline Used near command to calculate distance to nearest coral reef Used spatial join to assign permit grid cells to nearest town and obtain number of people in the town. Combinations of x and y used to capture spatial autocorrelation as described in text

Location

5

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Table 3 Summary of potential influences on numbers of permits per grid cell. The numbers in brackets summarise the total number of variables per matrix.

Permit type Resource extraction Research and education Tourism and special events Access Infrastructure Pest control All permits

locations and their population sizes (Table 2). We used variance partitioning, run in R with the varpart command from the vegan library (Oksanen et al., 2011), to compare the influences of the different kinds of variable (Table 3) on the numbers of permits per grid cell. Variance partitioning holds the influences of some variables constant while exploring the effects of others, allowing the user to apportion variance within the data set to both individual and interaction effects between different kinds of variable (Legendre and Legendre, 1998; Oksanen et al., 2011). In this case, spatial autocorrelation is a potentially confounding variable; we included the x and y coordinates of each centroid as well as three non-linear combinations of the coordinates (x2, y2, and xy), following Borcard et al. (1992), to absorb variance in permit numbers due to spatial proximity between grid cells and spatial gradients (e.g., north to south). The variables comprising each of the explanatory matrices that we compared are described in Table 2. We set the scale command in varpart to ‘TRUE’ for all analyses, so that all data were standardized in the analysis and hence not biased by their individual magnitudes. We first treated all six different kinds of permission as a single ‘response data’ matrix, then repeated the variance partitioning analysis using the number of permissions per grid cell for each of the six different permit types as individual response variables. This allowed us to understand general geographic patterns in permission numbers as well as individual idiosyncrasies by permit type.

Minimum

Median

Mean

Maximum

9 7 4 510 2 1 534

17 16 17 589 4 1 642

17.67 13.85 21.83 693.7 7.637 2.244 757.6

118 51 357 1241 88 32 1715

4000

Expected trend in permit numbers

3500

Date of data download: June 2017

3000 2500 2000 1500

Permits issued before June 2017

1000

2032

2027

0

2022

500

2017

x coordinate; y coordinate; x ∗ y; x2; y2 (4) Distance to nearest town; number of people in nearest town (2) Distance to nearest coral reef or island; distance to mainland (2)

2012

Location Population Biophysical

2007

Variables in matrix

2002

Matrix name

Table 4 Numbers of permits per 2 × 2 km grid cell for different permit types, as displayed in Fig. 2. Note that the highest numbers of permits for each activity did not necessarily occur in the same cells, and so the sum of the ‘Maximum’ column is not the same as the value for ‘All permits’, which derives from the single grid cell with the greatest number of permits.

Fig. 1. Changes in the total number (solid black line) and newly issued numbers (dotted blue line) of valid permissions (y-axis) against time (x-axis). Data include 10,030 permissions from 7478 permits in the GBRMPA permits database to June 2017. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3. Results

When comparing permission numbers per grid cell (Fig. 2), the numbers of all permission types were strongly and significantly correlated with the numbers of all other permission types (Spearman's correlation, p < 0.000, df = 87,904). All correlations were positive except for that between resource extraction and research and education, which was negative. Due to the large sample size and high autocorrelation inherent in this kind of data, the p-values of relationships are not a particularly good guide to their interpretation; but the magnitudes of the coefficients (Table 5) suggest that the location of resource extraction permissions was weakly correlated with the locations of tourism and special events permissions; more strongly correlated with locations of permissions for access and infrastructure; and strongly correlated with locations of permissions for pest control efforts (pest control permissions are mainly for Crown-of-Thorns Starfish and Drupella snails). Principal components analysis of the data indicated that 95.15% of the variance in permission numbers could be explained by a single component, heavily weighted on access. The second component explained 4.53% of variance and was dominated by tourism and special events permissions. Access, and the regulation of access as a management tool appears to be dominant in relation to both the numbers of permissions issued and in its role as a pre-condition for other activities. Access is often granted to areas that may or may not be used by the permittee, to provide them the flexibility to manage their activity without needing to apply for frequent updates or changes (note, however, that access is only granted to requested areas). Variance partitioning using all permission data as the response matrix (i.e., a matrix in which grid cells were the rows and columns were the numbers of unique permissions in each of the six classes)

We had originally anticipated that all permits would refer to either the entire GBR or to the map of permissible activity zones that is familiar to most users of the GBR. In practice, however, we required 20 different shapefiles (Table 1) from three different agencies (GBRMPA, Queensland Parks, and Queensland Fisheries) to represent all of the permit data. Queensland Fisheries data were needed to identify the boundaries of the harvest fisheries and collecting permits for Tropical Rock Lobsters, corals, Trochus (Top Shell Snails), sea cucumbers, and marine aquarium fishes. Additional data layers were partially a result of the presence of three localised, finer-scale, more effort-intensive management plans within the GBR: respectively, for tourism hotspots near the Whitsundays, Cairns, and Hinchinbrook. Some further complexity was introduced by the use of maps describing fisheries that extend beyond the GBR and maps of estuarine and freshwater features. The total number of permissions per 2 × 2 km grid cell ranged from 534 to 1715 (Table 4). The number of access-related permissions (e.g., vessels, aircraft, ferries; see full list in Appendix 1) was an order of magnitude greater than that of other classes. The number of permits of all types that were valid over the time period 2007–2017 increased rapidly over time (Fig. 1), indicating a steadily increasing demand for permits relating directly to use of the ecosystem services provided by the GBR. In 2007, the earliest date from which permits were issued was 2002. Permit validity in the data set ranged from 2002 to 2036. The data end in July 2017, at the peak of the curve in Fig. 1; the appearance of a reduced rate of permit applications in 2017 is an artefact of only having half a year's data for 2017. The long tail of the distribution describes the time lags that are inherent in the permitting system. Permits had an average lifespan of 6.9 ± SD 3.3 years; and some of the permits that were valid in 2017 will only expire as late as 2036. 6

7

(e)

(b)

(f)

(c)

Fig. 2. Numbers of permits by 2 × 2 km grid cell across the Great Barrier Reef Marine Park for the six different permit types discussed in the paper: (a) resource extraction, (b) research and education, (c) recreation and tourism, (d) access and transport, (e) infrastructure, and (f) pest control.

(d)

(a)

G.S. Cumming and K.A. Dobbs

Biological Conservation 237 (2019) 3–11

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G.S. Cumming and K.A. Dobbs

Table 5 Spearman's correlation coefficients between the numbers of different types of permits by grid cell across the GBR. All correlations were statistically significant (n = 87,906, p < 0.000). Resource extraction

Research and education

Tourism and special events

Access

Infrastructure

Pest control

−0.38 0.10 0.14 0.14 0.45

1.00 0.52 0.40 0.42 0.05

1.00 0.82 0.89 0.80

1.00 0.60 0.59

1.00 0.81

1.00

Research and education Tourism and special events Access Infrastructure Pest control

(a)

LOC X1

POP X2

0.20

0.14

(b)

X1 LOC

X2 POP

[a]

0.05

[d]

[g]

0.03 0.04

[e]

[f]

0.00

[c]

0.01

X3 BIO

[b]

Residuals = 0.51

X3 BIO

Fig. 3. Visual depiction of results from variance partitioning of explanatory variables for (a) all six types of permit data; and (b) generalised reporting scheme adopted in Table 6. As described in Table 3 of the methods section, matrices considered as explanatory variables were: LOC, location; POP, population; BIO, biophysical. Numbers represent the proportion of variance explained by each matrix, either independently with other effects held constant (numbers in circle centres) or through interaction effects with other effects held constant (numbers in circle overlaps).

Residuals = [h]

efficient processes. As depicted in Fig. 2, permit hotspots fell within the more intensively managed tourism locations, particularly the Whitsundays. The range of different spatial data layers that was needed to capture the permit data came as a surprise, but arises logically from the geographic intersection of three different agencies (GBRMPA, Queensland Parks and Wildlife Service, and Queensland Fisheries) as well as the fact that the Great Barrier Reef Marine Park covers 344,400 km2. Consideration of permission numbers by type showed that the highest demand for permits arose from the need for access. Access is a limiting factor for other activities, in the sense that they cannot occur without it; as might be expected from this obvious synergy, access permissions were highly correlated with those for both infrastructure and tourism. Permissions for resource extraction were negatively correlated with permissions for research and education, as might be expected, but not with those for tourism and special events. Interestingly, this suggests that extractive uses are more compatible with tourism than with scientific research. It also suggests that the majority of research on the GBR focuses on ecosystems with fewer commercial activities, implying a possible need for more research in heavily used (e.g., for fishing and boating) locations (e.g., see Simpson et al., 2016; Berry et al., 2017). Analysis of spatial effects on permission numbers indicated a lower influence of the biophysical environment than expected. Neither of the biophysical variables considered in this category (proximity to the coast and proximity to reefs and islands) appeared to be useful predictors of non-research permissions when coordinates were also included in the analysis. The unexpectedly low geographical influence of reefs on permissions suggests the presence of an un-measured, broader-scale social-ecological influence on permitting demand. For tourism and tourism-related permissions, research in other systems has shown that easy access via airports and highways is critical for the economic viability of nature-based tourism (Knežević Cvelbar et al., 2015; De Vos et al., 2016), and the less accessible areas north of Cairns may be unable to compete with the southern GBR for clients, many of whom are nonAustralians in the 25–29 year old age group (Coghlan, 2012). Additionally, resource users (and tourists) who consider operating in or visiting the northern GBR may be discouraged by the higher presence of potentially dangerous marine organisms, particularly irukandji and box

indicated that the considered variables cumulatively explained 49% of variance in the data (Fig. 3). Of this amount, 41% was explained either by location (as defined in Table 3) or by interactions of other variables with location. The interaction effect between location and population was the strongest effect, explaining an additional 14% of variance. Location alone explained 20% of variance in permission numbers, followed by population (5%). Biophysical variables explained only 1% of variance in overall permission numbers and a total of 8% when interaction effects with other variables were included. Considering numbers of different permission types per 2 × 2 km grid cell as individual response variables provided additional insights into the nature of spatial influences on permission numbers (Fig. 3, Table 6). Table 6 shows that as for the aggregated analysis, the dominant influence explaining variance in permission numbers was location. The only permission type that was strongly influenced by the biophysical environment was research and education, through its interactions with location (20%) and its additional interaction with both location and population (15%). With 77% of variance in research and education permission numbers per 2 × 2 km grid cell explained by the variables in the analysis, these numbers could be easily predicted through multivariate regression. With the exception of tourism and special events permissions, whose variance was only weakly explained (15%), > 40% of variance in numbers of the other permission types could be explained by the variables considered in this analysis. 4. Discussion Our analysis offers novel insights into the use of permits to manage a large marine protected area. Numbers of permissions per 2 × 2 km grid cell in the GBR seemed relatively high, ranging from 534 to 1715. The rapid, non-linear increase in numbers of issued permits over time suggests increasing demand for the various uses and entry provided by the GBR, given that there has been no particular change in permitting policy over the period of our analysis (e.g., introducing new requirements for permits for activities that did not previously require them would offer an alternative hypothesis). If this trend continues, coping with increasing demand will require either corresponding increases in permit processing capacity or better use of technology to create more 8

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0.00 0.00 0.02 0.01 0.01 0.03

0.06 0.47 0.04 0.14 0.08 0.06

0.00 0.00 0.02 0.02 0.00 0.02

0.09 0.20 0.02 0.02 0.00 0.02

0.04 0.15 0.00 0.19 0.08 0.08

0.59 0.23 0.85 0.47 0.59 0.36

0.41 0.77 0.15 0.53 0.41 0.64

jellyfish (Fenner and Harrison, 2000) and estuarine crocodiles (Read et al., 2005). For commercial non-tourism activities, the lack of ports and commercial centres in far north Queensland is again likely to reduce permit demand. Our results carry some interesting implications for management of the GBR. Permit demand from 2007 to 2017 appears to have been more related to human population numbers and location than to the habitat structure of the biophysical environment. However, many activities (e.g., commercial tourism and fisheries operations) are fundamentally dependent on the presence of reefs and their associated fauna. The availability of adequate reefs for these activities is not currently a limiting factor. If it becomes one, then the relationships that we have described may change, with ecosystem habitat structure becoming a more dominant influence on permit applications. As the GBR undergoes rapid ecological change, due to an increasing frequency of marine heatwaves (Hughes et al., 2017b), there is a high potential for a spatial mismatch between the requirements and expectations of human users and the ability of the environment to provide ecosystem services (Cumming et al., 2006; Mills et al., 2010; Maciejewski et al., 2015). The underlying drivers of permit demand and the relationship between the biophysical environment and its use by people may also start to change (Crouzat et al., 2016). The future dynamics of different kinds of use, and the degree to which people either adapt to change and compensate for its impacts versus altering their spatial patterns of resource use, suggest interesting areas for further study. An obvious example of the kinds of challenge faced by the GBR is the loss of large areas of old-growth coral to coral bleaching in the northern section of the GBR (Hughes et al., 2017b). This has already started to create challenges for tourism operators in the Cairns region, where bleaching has been widespread and some previously favoured destinations (with their associated investments in infrastructure) no longer provide high quality diving and snorkelling experiences (Prideaux et al., 2018). If the southern end of the GBR were to bleach, the number and nature of tourism operations near to larger population centres would presumably have to change rapidly, and responsively. The time lags in the permitting system – with increasing demand, and some permits (e.g., pontoon infrastructure) being valid for up to 22 years – may, however, make it difficult for both industry and GBRMPA to respond nimbly and proactively to environmental change. Amending permits to include additional locations is possible; revoking permits can only be done because of non-compliance or environmental harm, as outlined in the Great Barrier Reef Marine Park Regulations 1983. Compulsory acquisition of permits is not allowed under the legislation. These factors have the potential to create additional mismatches between the temporal and spatial scales of resource use and management. As discussed in more depth by Bellwood et al., 2019 (under review, this 2019), responding to changes in coral reef socialecological systems is a challenging problem that will require managers and governments to develop ways of both managing change at scales greater than LMPAs, and coping more proactively with cross-scale dynamics and emerging scale mismatches. Regularly updated analyses of permit data, and tracking of changes in the number and location of requested and issued permissions, have the potential to offer a valuable and currently unexploited way of detecting longer-term change in human uses of the GBR. More generally, permit data provide a window for managers into the ways in which users of a large, multi-use protected area perceive and expect to use or access its resources. Our data provide insights into intended use but not into actual use of natural resources. An obvious and potentially useful next step in this analysis would be to compare spatial data on permits with spatial data on actual use patterns within the GBR, for example by linking to actual use undertaken by permitees. In addition to offering a first summary of patterns in the kind of regulation that is likely to be required at LMPAs across the globe, our analysis shows how permit data can offer detailed, spatially explicit perspectives on the social-ecological relationships between resources and people, providing a valuable

0.27 0.19 0.06 0.12 0.18 0.38 Resource extraction Research and education Tourism and special events Access Infrastructure Pest control

0.02 0.05 0.03 0.03 0.06 0.13

g Interaction of LOC + POP + BIO f BIO + LOC | POP e POP + BIO | LOC d LOC + POP | BIO c BIO | LOC + POP b POP | LOC + BIO a LOC | POP + BIO Response variable

Table 6 Absolute values of different coefficients. The meaning of each coefficient is most easily grasped by consideration of Fig. 3. LOC, location; POP, population; BIO, biophysical.

h Residual

All

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G.S. Cumming and K.A. Dobbs

complement to other ways of understanding resource dependence (e.g., Marshall et al., 2017). As emphasized by Gruby et al. (2016), LMPA creation and governance globally are still at an early stage. Our analysis suggests that early consideration and development of a robust permitting process, and creation of approaches to regularly extracting and summarising relevant information on permit locations and trends, can play a valuable role in their management.

providing the permit data and to the Great Barrier Reef Marine Park Authority for permission to analyse it. We thank Miin Chua for her help in tracking down data sets and linking permit data to maps, and the members of various governmental agencies who helped us to locate and understand the data. We particularly thank Rhonda Banks (GBRMPA), Len Olyott (Queensland Parks and Wildlife Service), and Genevieve Phillips, Danielle Stewart and Tu Nguyen from Queensland Fisheries. This research was funded by the ARC Centre of Excellence for Coral Reef Studies and a James S. McDonnell Foundation grant to GC.

Acknowledgements We are grateful to Dave Leverton for his assistance in extracting and

Appendix 1. Summary of permit types that were aggregated to form the six classes of permits analysed in the paper Operation type (45 classes)

Aggregated type (6 classes)

Aquaculture Collecting Commercial activity Extractive research Fishing vessel Take of protected species Fishing Harvest fishery Commercial research Education Handling turtle hatchlings Non-extractive research Research vessel Research Bareboat Barge + tourism Beach hire Fireworks Guided tours Photography Tourism Barge Cargo Charter aircraft Charter vessel Craftless Extended aircraft Extended vessel Ferry service Fuel transfer Navigating a ship Special aircraft Special vessel Standard aircraft Standard vessel Support service Tug Cruise ship Rivers and streams Carrying out works Facility Marker Mooring Pest removal

Commercial resource extraction Commercial resource extraction Commercial resource extraction Commercial resource extraction Commercial resource extraction Commercial resource extraction Commercial resource extraction Commercial resource extraction Education and research Education and research Education and research Education and research Education and research Education and research Non-extractive tourism Non-extractive tourism Non-extractive tourism Non-extractive event Non-extractive tourism Non-extractive tourism-related use Non-extractive tourism Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Access and transport Built infrastructure Built infrastructure Built infrastructure Built infrastructure Pest removal

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