A comparison of threats, vulnerabilities and management approaches in global seagrass bioregions

Abstract

Global seagrass habitats are threatened by multiple anthropogenic factors. Effective management of seagrasses requires information on the relative impacts of threats; however, this information is rarely available. Our goal was to use the knowledge of experts to assess the relative impacts of anthropogenic activities in six global seagrass bioregions. The activities that threaten seagrasses were identified at an international seagrass workshop and followed with a web-based survey to collect seagrass vulnerability information. There was a global consensus that urban/industrial runoff, urban/port infrastructure development, agricultural runoff and dredging had the greatest impact on seagrasses, though the order of relative impacts varied by bioregion. These activities are largely terrestrially based, highlighting the need for marine planning initiatives to be co-ordinated with adjacent watershed planning. Sea level rise and increases in the severity of cyclones were ranked highest relative to other climate change related activities, but overall the five climate change activities were ranked low and experts were uncertain of their effects on seagrasses. The experts’ preferred mechanism of delivering management outcomes were processes such as policy development, planning and consultation rather than prescriptive management tools. Our approach to collecting expert opinion provides the required data to prioritize seagrass management actions at bioregional scales.

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A comparison of threats, vulnerabilities and management approaches in global seagrass
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2012 Environ. Res. Lett. 7 024006
(http://iopscience.iop.org/1748-9326/7/2/024006)
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IOP PUBLISHING ENVIRONMENTAL RESEARCH LETTERS
Environ. Res. Lett. 7 (2012) 024006 (8pp) doi:10.1088/1748-9326/7/2/024006
A comparison of threats, vulnerabilities
and management approaches in global
seagrass bioregions
Alana Grech
1
, Katie Chartrand-Miller
2
, Paul Erftemeijer
3
,
Mark Fonseca
4
, Len McKenzie
2
, Michael Rasheed
2
, Helen Taylor
2
and
Rob Coles
2
1
ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville QLD 4811,
Australia
2
Northern Fisheries Centre, Fisheries Queensland, Cairns QLD 4870, Australia
3
Sinclair Knight Merz, Perth WA 6000, Australia
4
NOAA/NOS/NCCOS Center for Coastal Fisheries and Habitat Research, Beaufort, NC 28516, USA
E-mail: Alana.Grech@jcu.edu.au
Received 2 February 2012
Accepted for publication 20 March 2012
Published 18 April 2012
Online at stacks.iop.org/ERL/7/024006
Abstract
Global seagrass habitats are threatened by multiple anthropogenic factors. Effective
management of seagrasses requires information on the relative impacts of threats; however,
this information is rarely available. Our goal was to use the knowledge of experts to assess the
relative impacts of anthropogenic activities in six global seagrass bioregions. The activities
that threaten seagrasses were identified at an international seagrass workshop and followed
with a web-based survey to collect seagrass vulnerability information. There was a global
consensus that urban/industrial runoff, urban/port infrastructure development, agricultural
runoff and dredging had the greatest impact on seagrasses, though the order of relative impacts
varied by bioregion. These activities are largely terrestrially based, highlighting the need for
marine planning initiatives to be co-ordinated with adjacent watershed planning. Sea level rise
and increases in the severity of cyclones were ranked highest relative to other climate change
related activities, but overall the five climate change activities were ranked low and experts
were uncertain of their effects on seagrasses. The experts’ preferred mechanism of delivering
management outcomes were processes such as policy development, planning and consultation
rather than prescriptive management tools. Our approach to collecting expert opinion provides
the required data to prioritize seagrass management actions at bioregional scales.
Keywords: expert elicitation, marine planning, prioritisation, seagrass, threat assessment,
vulnerability assessment, management
S Online supplementary data available from stacks.iop.org/ERL/7/024006/mmedia
1. Introduction
Seagrasses are one of the most productive ecosystems on
earth (Duarte and Chiscano 1999) and provide a variety
of ecosystem services including fisheries habitat, coastal
protection, and nutrient recycling (Cullen 2007). Seagrasses
have been damaged and destroyed in many parts of the world
(Short and Wyllie-Echeverria 1996, Larkum et al 2006) as a
result of anthropogenic activities (Cambridge and McComb
1984, Coles et al 2003, Waycott et al 2009). Globally, 15%
of seagrass species are threatened (Randall Hughes et al
2009, Short et al 2011) and seagrass habitats have declined
11748-9326/12/024006+08$33.00
c

2012 IOP Publishing Ltd Printed in the UK

Environ. Res. Lett. 7 (2012) 024006 A Grech et al
Figure 1. The six seagrass specific geographic bioregions of Short et al (2007) used to segregate workshop participants and survey
respondents into sub-groups that corresponded to their knowledge and expertise.
worldwide at a rate of 110 km
2
yr
−1
between 1980 and
2006 (Waycott et al 2009). The causes of this decline vary
globally (Orth et al 2006) due to multiple factors including
local species resilience, the nature of anthropogenic activities,
and the frequency and scale of exposure to those activities.
Quantitative data on the relative impact of anthropogenic
activities is vital to the management of seagrasses as it
can direct the strategic deployment of limited resources
(Cleary 2006). Wilson et al (2007) found that targeting
management intervention to activities with the highest impact
can be more beneficial to achieving conservation goals than
other management approaches. However, information on how
multiple activities impact on seagrass habitats and species are
rarely available, especially at broad spatial scales such as for
global bioregions (Wilson et al 2005). A major cause of this
data deficiency is the limited ability of empirical studies to
evaluate the impact of multiple activities due to time, expertise
and cost constraints (Crain et al 2008). The commonly
reported lists of anthropogenic activities that have an impact
on seagrass are from compilations of different studies (Short
and Wyllie-Echeverria 1996, Short et al 2001, Orth et al 2006)
and are referenced routinely without questioning the relevance
of that list or the order of importance of the activities. The data
supporting that order, and whether the list that is referenced
is applicable to a particular location, scale or issue is often
not available. When stated as an overarching global effect, for
example, nutrient over-enrichment and sediment loads have
been described as the most important anthropogenic cause of
seagrass decline in coastal waters (Short et al 2001, Orth et al
2006). The scale and detail of data to support that assertion
and how well the data represents all locations in the world
where seagrasses are found remains undefined. The literature
is also biased to shallow coastal seagrasses within developed
regions which are readily accessible and where there are more
resources available for research and monitoring (Fonseca et al
2008).
Expert knowledge is fundamental to conservation
decision making (Burgman 2005, Martin et al 2012),
especially when actions are required before uncertainties
can be resolved (Sutherland 2006, McBride and Burgman
2011). Structured approaches to expert elicitation provide
a transparent and explicit process to identify and compare
diverse anthropogenic activities in data-poor scenarios
(e.g. Halpern et al 2007, Selkoe et al 2008, Donlan et al
2010, Teck et al 2010). Our objective was to inform seagrass
management needs across all seagrass bioregions using a
structured approach to bring together expert knowledge on
the relative impact of multiple anthropogenic activities. The
assessment was conducted at the scale of seagrass bioregions
(Short et al 2007) so that the outputs of our assessment were
applicable at the regional (management) scale. We used the
outputs of the assessment and a follow-up expert workshop
to explore regional similarities and differences in seagrass
management approaches.
2. Methods
2.1. Expert workshop
We hosted an expert workshop to identify the anthropogenic
activities that threaten seagrasses at the 8th International
Seagrass Biology Workshop (ISBW8) in September 2008
at Bamfield, Canada. The workshop was attended by 122
participants from academic institutions, government agencies
and non-government organizations with expertise in seagrass
ecology, biology, monitoring, threats and management. The
workshop participants were divided into groups based upon
their regional knowledge of seagrasses in accordance with
the six seagrass bioregions identified by Short et al (2007).
Temperate North Atlantic, Tropical Atlantic, Mediterranean,
Temperate North Pacific, Tropical Indo-Pacific and Temperate
Southern Oceans (figure 1). The groups were asked
to: (1) identify the anthropogenic activities that threaten
seagrasses within their bioregion; and (2) rank the activities
in order of their relative impact. Experts from different
parts of the world used different nomenclature for the same
2

Environ. Res. Lett. 7 (2012) 024006 A Grech et al
Table 1. Ranking system for the five vulnerability factors (Halpern et al 2007, Selkoe et al 2008).
Score Scale Frequency Functional impact Resistance Recovery time Certainty
0 No impact Never occurs No impact Not applicable No impact Not at all certain
1 <1 km
2
Rare <25% of species High resistance <1 year Low certainty
2 1–10 km
2
Occasional 25–50% of
species
Medium
resistance
1–10 years Moderate certainty
3 10–100 km
2
Annual or
regular
50–100% of
species
Low resistance 10–100 years High certainty
4 100–1000 km
2
Persistent >100 years Very certain
5 1000–10 000 km
2
6 >10 000 km
2
anthropogenic activity (e.g. coastal development, construction
and coastal structures were used to describe the threat
of urban/port infrastructure development). We devised a
common nomenclature to identify anthropogenic activity
categories and used this common identifier for ease of
comparison across bioregions (supporting material 1 available
at stacks.iop.org/ERL/7/024006/mmedia).
2.2. Web-based vulnerability assessment
Following ISBW8, we assessed the relative impact of
anthropogenic activities using the approach of Halpern et al
(2007). The approach requires experts to provide a rank value
(score) for five attributes that determine the vulnerability of
seagrasses to anthropogenic activities, and an estimate of their
uncertainty (table 1). In comparison with the simple ranking
exercise of the ISBW8 workshop, this process encourages
evaluation of the components that contribute to seagrass
vulnerability. We collected scores from experts using a
web-based survey tool. The survey included questions on
the anthropogenic activities identified at the ISBW8 expert
workshop and an additional three climate change related
threats from Orth et al (2006) and Waycott et al (2007).
Invitations were emailed to the 122 participants from the
ISBW8 workshop. An additional 10 individuals with expertise
in bioregions that were not adequately represented at the
workshop were also invited to participate in the survey
to ensure representation of the whole expert community
(Armstrong 2006). The survey contained information on
the aims and objectives of the study and a description
of the five vulnerability factors, uncertainty estimates and
scoring approach. Survey respondents were asked to stipulate
their affiliation (academic institution, government agency and
non-government organization) and the seagrass bioregion that
their answers applied to (Short et al 2007, figure 1). At the end
of the survey, respondents were asked to indicate if the survey
was easy to understand (yes, all of the time; yes, sometimes;
no, not very often; no, not at all).
A hierarchical cluster analysis was used to detect outliers
in the survey respondents. The standard error and coefficient
of variation (CV) in vulnerability scores across responses
was used to assess the degree of consensus among experts.
We assessed differences in the mean vulnerability scores
of experts when grouped by their institutional affiliation
and bioregion (ANOVA) and gender (t-test) and evaluated
the effect of sample size on the vulnerability scores within
bioregions using a linear regression.
The rank values for the vulnerability factors of scale,
functional impact and resistance (table 1) were rescaled to
a 0–4 range by multiplying each by 4/6, 4/3 and 4/3
respectively, so that all factors had the same range of
values. Each vulnerability factor was assumed to have equal
weighting (after Halpern et al 2007, Selkoe et al 2008). We
combined the mean of the expert-derived scores of the five
vulnerability factors to create a single vulnerability score for
each anthropogenic activity in each bioregion and at a global
scale. The scores of experts were not weighted according to
age, experience, qualification etc as such approaches do not
provide better results than simply averaging scores across
all respondents (Clemen 1989). We used t-tests to assess
differences in vulnerability scores of individual activities both
within and across bioregions. Anthropogenic activities were
ranked by their vulnerability scores to allow a comparison
between the results of the web-based survey and the rankings
derived at the ISBW8 expert workshop.
2.3. Follow-up expert workshop
We hosted a follow-up workshop in November 2010 at the
9th International Seagrass Biology Workshop (ISBW9) in
Trang Province, Thailand to identify management options
to mitigate the impact of four anthropogenic activities. At
this follow-up workshop, the participants were divided into
their sub-regional groups. The location of the workshop in
South-East Asia had mostly scientists and managers from
the tropical Indo-Pacific bioregion (Australia, Indonesia,
Singapore and Malaysia, Thailand, the Philippines and
China).
3. Results
The web-based vulnerability survey received an above-
average response rate of 45% (total = 59) relative to similar
surveys (Halpern et al 2007) and to online surveys overall
(Cook et al 2000). Forty-two responses were from the staff
of academic institutions, nine were from government agencies
and eight were from non-government organizations (table 3).
The number of survey responses varied among bioregions,
with the Tropical Indo-Pacific receiving the most responses
(n = 22) and the Temperate North Pacific receiving the least
3

Environ. Res. Lett. 7 (2012) 024006 A Grech et al
Table 2. Rankings of the relative impact of multiple anthropogenic activities on seagrasses in six bioregions derived from the expert
workshop (EW) at ISBW8 and the vulnerability assessment (VA) (1 = most threatening activity). A dash (—) indicates that the
anthropogenic activity was not identified as a threat to seagrasses at the expert workshop.
Anthropogenic activity
Temperate
North
Atlantic
Tropical
Atlantic Mediterranean
Temperate
North
Pacific
Tropical
Indo-
Pacific
Temperate
Southern
Oceans Global
EW VA EW VA EW VA EW VA EW VA EW VA VA
Agricultural runoff 1 1 1 3 6 4 2 9 3 7 5 2 3
Aquaculture 8 6 — 13 4 5 3 8 7 5 4 5 6
Boat damage (commercial) — 12 8 — 10 — 12 10 8 7 8 7
Boat damage (recreational) 7 9 5 6 5 7 4 15 8 12 8 9 8
Changes in air temperature — 13 — 15 — 14 — 5 — 14 — 13 14
Changes in sea surface temperature — 7 — 12 — 13 6 2 — 10 — 12 10
Desalination plants — 17 — 18 9 12 — 18 — 15 3 10 17
Dredging 5 4 2 2 7 6 — 11 4 3 9 3 4
Elevated CO
2
and ocean acidification — 15 — 16 — 16 — 7 — 17 — 11 16
Fishing (other than trawling) 4 11 — 10 — 11 — 14 5 9 — 16 11
Increase in severity of tropical cyclones — 16 6 5 — 18 — 17 — 6 — 17 13
Invasive/introduced species — 10 — 14 8 9 8 10 11 18 2 14 15
Sea level rise — 3 — 9 — 17 — 3 — 16 — 15 12
Seagrass harvesting — 18 — 17 — 15 — 16 12 13 — 18 18
Shipping accidents (e.g. oil spills) — 14 4 7 — 8 — 6 9 11 — 6 9
Trawling 6 5 3 11 2 3 7 13 2 4 1 7 5
Urban/industrial runoff 3 2 — 1 3 2 5 4 6 1 6 1 1
Urban/port infrastructure development 2 8 — 4 1 1 1 1 1 2 10 4 2
(n = 5; table 3). However, we found no significant effect
of sample size on the vulnerability scores (F = 0.655, p =
0.464). The majority of respondents found the survey easy to
understand and complete (76%) with no effect of affiliation,
gender or bioregion.
The hierarchical cluster analysis revealed five clusters
(see supporting material 2 available at stacks.iop.org/ERL/
7/024006/mmedia). Four clusters represented the survey
respondents from four bioregions (Temperate North Atlantic,
Tropical Indo-Pacific, Mediterranean and Tropical Atlantic),
indicating a high similarity in scores from experts within those
bioregions. Survey respondents from the Temperate North
Pacific were within two clusters and respondents from the
Temperate Southern Ocean were scattered throughout the five
clusters.
We found no significant differences in vulnerability
scores among the three categories of affiliation (academic,
government and non-government; F = 1.080, p = 0.393).
There was also no significant relationship between gender and
the vulnerability scores of experts (F = 0.04, p = 0.346). As
indicated by the hierarchical cluster analysis, the bioregion of
survey respondents had a significant effect on vulnerability
scores (F = 1.615, p = 0.006). The values of the coefficient
of variation (CV) across the scores for the five vulnerability
factors (supporting material 3 available at stacks.iop.org/ERL/
7/024006/mmedia) revealed high variation in the scores for
climate change related activities and the vulnerability factor
‘scale’.
The vulnerability assessment identified urban/industrial
runoff as the greatest threat to seagrasses in three bioregions,
urban/port infrastructure development in two bioregions,
and agricultural runoff in one bioregion (tables 2 and
4). At a global scale, the vulnerability scores for urban
runoff, urban/port infrastructure development, agricultural
Table 3. Number of survey respondents in each bioregion and their
affiliation and gender category. NGO = non-government
organization.
Bioregion
Affiliation Gender
Academic
Government
Agency NGO Male Female
Temperate
North Atlantic
4 3 0 5 2
Tropical
Atlantic
8 1 2 6 5
Mediterranean 6 0 1 3 4
Temperate
North Pacific
3 1 1 3 2
Tropical
Indo-Pacific
16 3 3 14 8
Temperate
Southern Ocean
5 1 1 4 3
Total 42 9 8 35 24
runoff and dredging were significantly higher than the
vulnerability scores of the remaining anthropogenic activities
(p < 0.05); the vulnerability scores for seagrass harvesting
and desalination plants were significantly lower (p < 0.05).
The major differences in rankings between the vulnerability
assessment approach and the simple ranking approach of the
expert workshop were the elevation in rank of urban/industrial
runoff and the reduction in rank of trawling (table 2).
Of climate change related impacts the highest mean
vulnerability scores were a rank of 2 for changes in sea surface
temperature in the Temperate North Pacific and a rank of 3
for changes in sea level rise in the Temperate North Pacific
and Temperate North Atlantic (tables 2 and 4). The highest
ranks for other climate change factors were ranks of 5 and 6
for increases in tropical storm severity in the Tropical Atlantic
4

Environ. Res. Lett. 7 (2012) 024006 A Grech et al
Table 4. Vulnerability and certainty scores for 18 anthropogenic activities across six bioregions derived from expert opinion and a
web-based vulnerability assessment. VS = vulnerability score; C = certainty score; CV = coefficient of variation. Activities are organized
from the highest to lowest VS scores based on the global scale results.
Anthropogenic activity
Global
Temperate
North
Atlantic
Tropical
Atlantic Mediterranean
Temperate
North
Pacific
Tropical
Indo-
Pacific
Temperate
Southern
Oceans
VS C VS C VS C VS C VS C VS C VS C
Urban/industrial runoff 2.78 2.49 2.65 2.00 2.95 2.50 3.02 2.14 2.91 2.20 2.60 2.94 2.86 2.40
Urban/port infrastructure development 2.67 2.71 2.17 2.43 2.61 2.20 3.20 2.57 3.17 3.00 2.52 3.12 2.73 2.60
Agricultural runoff 2.62 2.37 2.99 2.43 2.87 2.60 2.86 2.00 2.72 1.60 2.16 2.59 2.86 2.40
Dredging 2.56 2.76 2.60 2.43 2.89 3.11 2.31 2.29 2.57 2.00 2.38 3.12 2.78 2.80
Trawling 2.39 2.22 2.55 2.00 2.18 2.44 2.93 2.17 2.33 2.00 2.37 2.65 2.01 1.00
Aquaculture 2.32 2.30 2.33 2.86 1.99 1.56 2.74 2.29 2.74 1.80 2.25 2.71 2.30 2.00
Boat damage (commercial) 2.13 2.54 2.05 3.14 2.35 2.67 1.84 1.57 2.34 2.40 2.13 2.76 2.00 2.20
Boat damage (recreational) 2.12 2.69 2.17 2.86 2.47 3.00 2.21 2.29 2.26 2.00 1.85 2.88 1.99 2.40
Shipping accidents (e.g. oil spills) 2.10 1.86 1.76 1.57 2.41 2.67 2.12 0.57 2.78 2.00 1.87 2.12 2.07 1.60
Changes in sea surface temperature 2.03 1.65 2.30 1.86 2.17 2.00 1.18 0.29 3.17 1.80 1.90 2.07 1.89 1.20
Fishing (other than trawling) 1.98 2.27 2.07 2.43 2.22 2.20 1.69 1.71 2.30 1.80 1.98 2.76 1.52 1.80
Sea level rise 1.84 1.43 2.62 1.57 2.26 1.80 0.74 0.71 3.05 1.60 1.50 1.59 1.53 0.80
Increase in severity of tropical
cyclones
1.74 2.06 1.13 2.57 2.52 2.80 0.56 0.71 1.50 2.00 2.21 2.35 1.16 0.80
Invasive/introduced species 1.72 1.51 2.00 1.71 1.62 1.56 1.17 0.71 2.81 1.60 1.55 1.81 1.82 1.20
Changes in air temperature 1.72 1.80 2.10 1.86 1.73 1.80 2.08 1.86 2.67 2.20 1.23 1.76 1.59 1.40
Elevated CO
2
and ocean acidification 1.59 1.20 1.57 1.43 1.51 1.33 1.05 0.29 2.75 0.80 1.42 1.71 1.90 0.60
Desalination plants 1.31 1.48 0.54 1.50 0.99 1.40 1.66 1.57 1.03 2.20 1.54 1.35 1.97 1.20
Seagrass harvesting 1.22 2.45 0.42 3.00 1.14 2.33 1.16 1.83 1.62 2.20 1.60 2.76 0.82 1.80
Score mean 2.05 2.10 2.00 2.20 2.16 2.22 1.92 1.53 2.48 1.96 1.95 2.39 1.99 1.68
CV 22.2 23.4 35.0 24.9 26.4 24.7 43.0 50.1 23.6 22.6 20.9 23.0 28.6 40.9
and Tropical Indo-Pacific emphasizing regional differences
and differences between the temperate and tropical biomes
(table 2). The greatest range in mean vulnerability scores was
for climate change factors; sea level rise ranging from 3 to
17; and increases in the severity of tropical storms of 5–18
(table 2).
The Temperate North Pacific bioregion had the highest
mean vulnerability score across all anthropogenic activities
(2.5, CV 23.6), followed by the Tropical Atlantic (2.2,
CV 26.4) and Temperate North Atlantic (2.0, CV 35.0;
table 4) bioregions. In addition, the Temperate North Pacific
bioregion had the highest vulnerability score for seven of the
eighteen activities (table 4) and was the only bioregion whose
vulnerability scores were significantly higher than the global
average (F = 2.736, p = 0.014).
There was a significant, positive relationship between the
vulnerability and certainty scores of anthropogenic activities
across all bioregions (p = 0.01). Survey respondents had low
levels of certainty in their estimates of vulnerability scores
for climate change related impacts and desalination plants
(table 4).
At the follow-up workshop in 2010, 55 seagrass
experts were asked to identify management approaches to
mitigate the four top threats identified in the vulnerability
survey: urban/industrial runoff, urban/port infrastructure
development, agricultural runoff and dredging. 49% of the
responses were in favour of non-prescriptive approaches
(i.e. policy development, consultation, community awareness
and good planning; Coles and Fortes 2001). 26% of
responses suggested prescriptive options such as enforcement,
compliance and fines; and 25% reactive solutions e.g.
restoration, monitoring and mitigation.
4. Discussion
Seagrass communities are considered to be one of the
most highly threatened marine habitats along with coral
reefs, mangroves and salt marshes (Waycott et al 2009).
In this study, we assessed the relative impact of multiple
anthropogenic activities on seagrasses at the scale of global
bioregions by bringing together the expert knowledge of
seagrass researchers and managers. We used a vulnerability
assessment approach and a web-based survey in order to
reduce the biases associated with ranking exercises and to
capture the knowledge of experts across the globe.
Qualitative assessments of the relative impact of
anthropogenic activities are dependent on the subjective
judgements of the responding experts. Those judgements are
influenced by multiple factors including personal experience
and beliefs, cultural differences, and cognitive and judgement
bias (Carey et al 2005). These biases were demonstrated in
the ranking exercise at the expert workshop as participants
perceived anthropogenic activities with a high visual impact
such as trawling and dredging to have a greater impact on
seagrasses relative to other activities (table 2). When asked
to consider the components of risk (i.e. table 1) more diffuse
(and less visual) impacts such as urban/industrial runoff were
ranked higher. Systematic surveys of experts such as the
one used here better inform management as they are able
to overcome some of the problems associated with expert
5

Environ. Res. Lett. 7 (2012) 024006 A Grech et al
bias (e.g. Donlan et al 2010) and can identify key regional
differences that may need to be taken into account.
Seagrass scientists commonly use terms such as
‘modified sediment dynamics’ or ‘nutrients’ to identify
a threatening process (supplementary material 1 available
at stacks.iop.org/ERL/7/024006/mmedia; Short and Wyllie-
Echeverria 1996.) These terms may be useful in a biological
sense but are difficult to analyse in a risk-based management
approach as they are not clearly linked to the source of the
threatening activity. The common nomenclature developed in
this study (supporting material 1 available at stacks.iop.org/
ERL/7/024006/mmedia) links the threatening process with the
source of that process. This approach allows management
responses to target the specific anthropogenic activity and
to identify the industries and practices where intervention is
required (e.g. commercial shipping, land-based agriculture,
urban planning); and to identify the government and/or
management agencies with the power to implement change.
Seagrass meadows globally are found in shallow inshore
waters to a maximum depth of approximately 70 m (Coles
et al 2009). However most meadows are found in inshore
waters less than 10 m deep where their health and survival is
influenced by complex natural and human induced processes.
It is in this zone, where the land and sea meet, that seagrasses
are under pressure from their greatest threats: urban/industrial
runoff, urban/port infrastructure development, agricultural
runoff and dredging (tables 2 and 4). These activities are
largely terrestrially based, and our results highlight the
need for marine planning initiatives to be co-ordinated with
adjacent watershed planning (Alvarez-Romero et al 2011).
Programmes have been designed for land–sea planning to
control the effects of agricultural runoff (Gordon 2007).
However, urban and industrial land-use planning is rarely
co-ordinated with adjacent marine spatial planning initiatives
and this may be to the detriment of coastal species such as
seagrasses.
Our analysis showed only minor differences in the top
four ranked anthropogenic activities among the six bioregions
(tables 2 and 4). This agreement is remarkable considering
the diversity of countries, seagrass species and threatening
activities globally. The global consensus was not fully shared
by the Temperate North Pacific seagrass experts who ranked
seagrasses more vulnerable overall than other bioregions and
ranked climate change related activities as a greater threat
to seagrass than other regions. The difference in perceived
vulnerabilities may be related to regional topography and
species (the bioregion is unusual as having a predominance
of Phyllospadix (an outer coast, rocky substrate species) and
Zostera with a narrow depth range) but the true source of these
differences remains unclear, and should be explored in future
studies.
Most experts outside of the Tropical North Pacific
bioregion were uncertain about the impact of climate change
pressures, but perceived the likelihood of climate change
having an impact on seagrasses as low (table 4). There were
regional differences. Increased severity for tropical cyclones
was ranked fifth and sixth in the Tropical Atlantic and Tropical
Indo-Pacific regions respectively against a global average
rank of 13. Tropical storms are a regional issue for the
tropics and repeated impacts from cyclones are seen as an
important threat. Sea surface temperature rise and sea level
rise are ranked higher in the temperate regions than elsewhere.
The seagrass community sees climate change impacts as
having a variable impact on seagrasses around the world.
Climate interacts in complex ways with biophysical factors
and plant species ecology and this is reflected in vulnerability
scores. There are other regional differences such as the high
vulnerability score for trawling in the Mediterranean that are
likely to be related to specific seagrass species vulnerability.
Fishing activities (e.g. net-fishing) in the Tropical Indo-Pacific
were ranked higher than other bioregions, reflecting the
regional differences in the exploitation of seagrass fisheries
(Unsworth and Cullen 2010) and the nature of the fishing
activities (e.g. frequency and scale of the threat events). These
differences in relative vulnerabilities across species, activities
and regions are important to understand as otherwise expertise
on approaches for managing and protecting seagrass may not
easily transfer from one part of the world to another.
There was a greater degree of consensus among
experts on the relative impact of anthropogenic activities
that are easily measured and detected compared with
complex influences such as climate change related activities
(supplementary material 3 available at stacks.iop.org/ERL/
7/024006/mmedia). There is probably a bias towards the
understanding of local issues where those issues are familiar
to experts (e.g. effects of dredging; Erftemeijer and Lewis
2006) and a bias away from understanding impacts at a global
scale (i.e. climate change). This is supported by the CVs
for the vulnerability factor ‘scale’ which were higher than
for other factors. There is unfamiliarity with the concept
of scale, and being asked to evaluate processes at very
large (global) scales is a novelty for most scientists. This
poor understanding of how anthropogenic activities affect
seagrasses across changing spatial scales and the conceptual
difficulties in comparing the relative impact of large scale
diffuse processes with small scale high impact process is
rarely analysed in seagrass literature or taken in to account
in coastal management decisions.
There are bioregional, political, cultural and seagrass
species specific factors that determine the best methods to
influence decision makers (both private and government)
to modify terrestrial activities and reduce impacts on
adjacent seagrass ecosystems (Coles and Fortes 2001). It
is not possible to provide a single recipe for coastal and
watershed managers that would be applicable for protecting
seagrasses globally. Translating a complex, government
sponsored and expensive marine monitoring and marine
planning programme (that includes farmers, landholders and
reef lagoon users as stakeholders as well as scientists and
government land and marine managers) that is effective
for Australia’s Great Barrier Reef (Brodie et al 2012) to
a small Pacific Island nation is unlikely to be productive.
Most effective is likely to be a package of approaches that
includes a mix of methods tailored to the local political,
social and biological environment. However we found a
clear preference based on experience within the seagrass
6

Environ. Res. Lett. 7 (2012) 024006 A Grech et al
community for transparent consultative processes such as
policy development, planning and consultation as an approach
rather than a legal enforcement/compliance approach, and this
should be taken into account. Our follow-up workshop had a
participant bias to South-East Asia but it is also likely that
this region will have an increasing influence on the global
approach to coastal management in the coming decades.
5. Conclusions
This study is the first to assess the relative impact of multiple
anthropogenic activities on seagrasses in the six global
bioregions of Short et al (2007). The rank outputs improve
on the accepted seagrass management paradigms (e.g. Short
and Wyllie-Echeverria 1996, Short et al 2001, Orth et al 2006,
Waycott et al 2009) as they were derived using a vulnerability
assessment and the expert opinion of seagrass researchers and
managers across the globe. We found that the major threats
to seagrasses are largely terrestrially based, highlighting
the need for seagrass management to be co-ordinated with
adjacent watershed planning. Seagrass experts emphasize the
need for planning and consultative approaches to achieve
terrestrial management change. The outputs of our approach
can be integrated with spatial data in cumulative impact
assessments that identify sites for management action across
multiple spatial scales (Halpern et al 2008, Selkoe et al
2009, Grech et al 2011). Future research should focus on
regional differences in vulnerability, especially in disturbance
hotspots.
Acknowledgments
We thank all of our 132 colleagues for their input at the
expert workshop and the web-based survey. Funding was
provided in part by Fisheries Queensland and the ARC
Centre of Excellence for Coral Reef Studies, James Cook
University. This project received approval from the James
Cook University Human Research Ethics Review Committee
(approval number H3510).
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