Seascape ecology: Identifying research priorities for an emerging ocean sustainability science

Abstract

Seascape ecology, the marine-centric counterpart to landscape ecology, is rapidly emerging as an interdisciplinary and spatially explicit ecological science with relevance to marine management, biodiversity conservation and restoration. While important progress in this field has been made in the past decade, there has been no coherent prioritisation of key research questions to help set the future research agenda for seascape ecology. We used a two-stage modified Delphi method to solicit applied research questions from academic experts in seascape ecology and then asked respondents to identify priority questions across nine interrelated research themes using two rounds of selection. We also invited senior management/conservation practitioners to prioritise the same research questions. Analyses highlighted congruence and discrepancies in perceived priorities for applied research. Themes related to both ecological concepts and management practice, and those identified as priorities include seascape change, seascape connectivity, spatial and temporal scale, ecosystem-based management, and emerging technologies and metrics. Highest priority questions (upper tercile) received 50% agreement between respondent groups and lowest priorities (lower tercile) received 58% agreement. Across all three priority tiers, 36 of the 55 questions were within a ±10% band of agreement. We present the most important applied research questions as determined by the proportion of votes received. For each theme, we provide a synthesis of the research challenges and the potential role of seascape ecology. These priority questions and themes serve as a roadmap for advancing applied seascape ecology during, and beyond, the UN Decade of Ocean Science for Sustainable Development (2021–2030).

Full text

MARINE ECOLOGY PROGRESS SERIES
Mar Ecol Prog Ser
Vol. 663: 1–29, 2021
https://doi.org/10.3354/meps13661 Published March 31
1. INTRODUCTION
Seascapes are complex ocean spaces, shaped by
dynamic and interconnected patterns and processes
operating across a range of spatial and temporal scales
(Steele 1989, Levin 1992, Pittman 2018a). Rapid ad -
vances in geospatial technologies and the proliferation
of sensors, both above and below the ocean surface,
have revealed intricate and scientifically in triguing
© The authors 2021. Open Access under Creative Commons by
Attribution Licence. Use, distribution and reproduction are un -
restricted. Authors and original publication must be credited.
Publisher: Inter-Research · www.int-res.com
*Corresponding author: sjpittman@gmail.com
FEATURE ARTICLE
Seascape ecology: identifying research priorities
for an emerging ocean sustainability science
S. J. Pittman1,2,*, K. L. Yates3, P. J. Bouchet4, 5, D. Alvarez-Berastegui6, S. Andréfouët7,
S. S. Bell8, C. Berkström9,10, C. Boström11, C. J. Brown12, R. M. Connolly13,
R. Devillers14, D. Eggleston15, B. L. Gilby16, M. Gullström17, B. S. Halpern18,19,
M. Hidalgo20, D. Holstein21, K. Hovel22, F. Huettmann23, E. L. Jackson24, W. R. James25,
J. B. Kellner26, C. Y. Kot27, V. Lecours28, C. Lepczyk29, I. Nagelkerken30, J. Nelson21,
A. D. Olds16, R. O. Santos31, K. L. Scales16, D. C. Schneider32, H. T. Schilling33, 34,
C. Simenstad35, I. M. Suthers33,34, E. A. Treml36, L. M. Wedding1, P. Yates34,37, M. Young36
1Oxford Seascape Ecology Lab, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK
2Project Seascape CIC, Plymouth PL2 1RP, UK
Full author addresses are given in the Appendix
ABSTRACT: Seascape ecology, the marine-centric
counterpart to landscape ecology, is rapidly emerging
as an interdisciplinary and spatially explicit eco logical
science with relevance to marine management, biodi-
versity conservation, and restoration. While important
progress in this field has been made in the past de -
cade, there has been no coherent prioritisation of key
research questions to help set the future research
agenda for seascape ecology. We used a 2-stage mod-
ified Delphi method to solicit applied research ques-
tions from academic experts in seascape ecology and
then asked respondents to identify priority questions
across 9 interrelated research themes using 2 rounds
of selection. We also invited senior management/con-
servation practitioners to prioritise the same research
questions. Analyses highlighted congruence and dis-
crepancies in perceived priorities for applied research.
Themes related to both ecological concepts and man-
agement practice, and those identified as priorities in-
clude seascape change, seascape connectivity, spatial
and temporal scale, ecosystem-based management,
and emerging technologies and metrics. Highest-
priority questions (upper tercile) received 50% agree-
ment between respondent groups, and lowest priori-
ties (lower tercile) received 58% agreement. Across
all 3 priority tiers, 36 of the 55 questions were within a
±10 % band of agreement. We present the most im-
portant applied research questions as determined by
the proportion of votes received. For each theme, we
provide a synthesis of the research challenges and
the potential role of seascape ecology. These priority
questions and themes serve as a roadmap for advanc-
ing applied seascape ecology during, and beyond, the
UN Decade of Ocean Science for Sustainable Devel-
opment (2021−2030).
O
PEN
PEN
A
CCESS
CCESS
To understand why spatial patterns matter, seascape ecol-
ogy works with maps such as this seafloor terrain showing
the surface complexity of coral reef ecosystems at multiple
spatial scales
Image: Simon J. Pittman
KEY WORDS: Research priorities · Ecosystem-based
management · Sustainability science · Connectivity ·
Restoration · Spatial patterns

Mar Ecol Prog Ser 663: 1–29, 2021
ecological patterns and processes (Thrush et al. 1997,
Schneider 2001, Boström et al. 2011), some of which
are the result of human activities (Bishop et al. 2017,
Halpern et al. 2019). Despite progress in the collect-
ing, mapping, and sharing of ocean data, the gap be-
tween technological advancement and our ability to
generate ecological insights for marine management
and conservation practice remains substantial (Borja
et al. 2020, Claudet et al. 2020). For instance, funda-
mental gaps exist in our understanding of the multi-
dimensional spatial structure in the sea (Boström et al.
2011, Pittman 2018a, D’Urban-Jackson et al. 2020), and
the implications for planetary health and human well-
being (Claudet et al. 2020). A deeper understanding of
the multi-scale linkages between ecological structure,
function, and change can better support the design of
whole-system strategies for bio diversity preservation
and reduce the uncertainty around the consequences
of human activity. For example, in the design and
evaluation of marine protected areas (MPAs) and
habitat restoration, it is important to understand the
influence of spatial context, configuration, and con-
nectivity, and to consider the effects of scale (García-
Charton et al. 2004, Huntington et al. 2010, Olds et al.
2016, Gilby et al. 2018b, Proudfoot et al. 2020).
Questions focussed on these crucial, overlooked,
and typically complex spatial variables can be ad -
dressed through the integrative, multi-scale and pat-
tern-oriented conceptual framework of landscape
ecology (Turner 1989, Ray 1991, Wedding et al. 2011,
Pittman 2018b). Landscape ecologists seek to under-
stand the causes and consequences of spatial com-
plexity (i.e. process−pattern linkages) through the
application of pattern-oriented concepts, tools, and
techniques (Turner 2005, Wedding et al. 2011, Wu
2013). A landscape ecology perspective generates
different research questions focussed on different
patterns, and at different scales, than conventional
approaches in marine ecology. Such a perspective is
more than a simple shift in emphasis because it
requires a change in the way scientists conceptualise
nature and the way they conduct their investigations
(Wiens 1999). Landscape ecologists typically repre-
sent nature with distinct pattern-oriented constructs
such as patches, patch mosaics, and spatial gradients
in both 2-dimensional and multi-dimensional space
and time (Wiens et al. 1993, McGarigal et al. 2009,
Gustafson 2019). Landscape ecology concepts (e.g.
corridors, connectivity, core area, edges, fragmenta-
tion) now permeate mainstream terrestrial ecology
and conservation practice and feature prominently in
global biodiversity policy (Turner 2005, McAlpine et
al. 2010, Rees et al. 2018b, Dunn et al. 2019).
Seascape ecology draws heavily from conceptual
and analytical frameworks developed in landscape
ecology and focusses on understanding spatial
pattern− process linkages in marine environments
(Ray 1991, Robbins & Bell 1994, Irlandi & Crawford
1997, Boström et al. 2011, Pittman 2018b). Seascape
ecology is an emerging science, with a growing
cadre of ecologists worldwide increasingly applying
the concepts and techniques of landscape ecology
to the sea, generating new insights into the causes
and ecological consequences of seascape patterns
and processes (Pittman 2018a). Like landscapes,
seascapes are considered heterogeneous spaces con -
taining interacting components that typically exhibit
scale dependence, non-linear dynamics, feedback
loops, and emergent properties (Holling 1992, Levin
1992, Schneider 2001, Dajka et al. 2020). These sys-
tems properties present diagnostic attributes for
understanding structure− function relationships and
evaluating system status that are key to imple-
mentation of ecosystem-based management (EBM)
(Levin & Lubchenco 2008, Parrott & Meyer 2012).
Like landscape ecology, seascape ecology focusses
on what we refer to here as the ‘4Cs’: context, con-
figuration, connectivity, and the consideration of
scale, an all-pervading concept. The term ‘config-
uration’ is used here as a broad class of spatial
structure that encompasses the arrangement of
patches, edges, and ecotones as represented in 2-
dimensional habitat maps and the 3-dimensional
structure of the water column, sea surface, and
seafloor topography (Fig. 1). A central tenet in land-
scape ecology is that the spatial configuration of
landscapes is intertwined with ecological function
such that when the former changes, the latter does
as well (Turner 1989, Bell et al. 1991, Wiens et al.
1993).
As an ecological science, landscape ecology has
evolved from multiple strands of pattern-oriented
eco logical and geographical thinking including island
biogeography theory (MacArthur & Wilson 1967),
which stimulated pioneering research on patchiness
in terrestrial and intertidal systems, on islands, and
across the pelagic ocean (Simberlo & Wilson 1969,
Steele 1978, Bormann & Likens 1979, Paine & Levin
1981). Early investigation of patch configuration in
shallow subtidal areas used natural experiments
and artificial structures to explore the influence of
patch size and isolation on faunal recruitment to
determine whether marine reserves should be a sin-
gle large patch or several small patches (e.g. sea-
grasses: McNeill & Fairweather 1993; patch reefs:
Schroeder 1987). At the time when landscape ecol-
2

Pittman et al.: Priority research for seascape ecology
ogy emerged as an ecological science, observations
of fish movements were beginning to shed light on
the influence of seascape configuration on func-
tional connectivity across tropical patch mosaics (i.e.
mangrove, seagrass, coral reefs) (Ogden & Gladfelter
1983, Birkeland 1985, Parrish 1989). Over the past
30 yr since the term ‘seascape ecology’ (sensu Ray
1991) first entered the scientific literature, steady
progress has been made in investigating the core
principles of landscape ecology in the marine envi-
ronment. Research has primarily focussed on ben-
thic seascapes, sometimes re ferred to as bentho -
scapes (Zajac et al. 2000, Brown et al. 2011, Proud foot
et al. 2020), or marine landscapes, and most often
applied to shallow coastal areas (Robbins & Bell
1994, Pittman et al. 2004, Connolly & Hindell 2006,
Jackson et al. 2006, Boström et al. 2011, Bell & Fur-
man 2017). Renewed focus on ‘ocean landscapes’
(sensu Steele 1989), now referred to as pelagic sea-
scapes (Alvarez-Berastegui et al. 2016, Hidalgo et
al. 2016, Kavanaugh et al. 2016, Scales et al. 2018),
and on seascape genetics (Selkoe et al. 2016) and
seascape economics (Barbier 2018) is broadening
the thematic scope of seascape ecology.
Data availability is also becoming less of a barrier
to progress in seascape ecology as reliable marine
geospatial data increase in quality, resolution, and
diversity; but continued improvements to data access
are crucial to facilitate greater progress (Huettmann
2011, Pendleton et al. 2019). At sea, international and
multi-sectoral efforts for seafloor mapping are gradu-
ally filling gaps and updating the global bathymetry
with high-resolution data (e.g. Seabed 2030 Project,
Wölfl et al. 2019). Simultaneously, Earth observation
monitoring systems capture and integrate huge vol-
umes of diverse marine data to address pressing
societal needs (Bax et al. 2019). The UN Decade of
Ocean Science for Sustainable Development (2021−
2030) will accelerate marine spatial data acquisition
(Claudet et al. 2020) and further enable the develop-
ment of seascape ecology as a sustainability science
for the ocean. The effective application of an integra-
tive multi-scale conceptual and operational frame-
work is required for the interpretation of complex
3
Fig. 1. Multi-dimensional seascape. A conceptualisation of pattern-forming structure in the ocean from the seafloor to the sea
surface. Physical, chemical, and biogenic variables generate measurable, sometimes predictable, and often interconnected
seascape structures such as surface topography, boundary layers, sediment plumes, plankton patches, and patch mosaics
(adapted from Pittman 2018b)

Mar Ecol Prog Ser 663: 1–29, 2021
4
data into knowledge and insight needed to support
transformative actions.
Although interest in seascape ecology is increasing
globally (Pittman 2018b), there has been no coherent
collaborative prioritisation of key research questions
to help guide the future research agenda for applied
seascape eco logy. Through a consultative process,
we asked seascape ecologists to formulate and then
prioritise important applied research questions that
would advance marine biodiversity conservation and
sustainable de velopment over the next decade. To
bridge science and practice, we also invited practi-
tioners of marine management, marine spatial plan-
ning, and conservation to prioritise important re -
search questions (henceforth 'practitioners'). We used
a 2-stage modified Delphi approach (Parsons et al.
2015, Yates et al. 2018) to make the process system-
atic and democratic (i.e. private voting). Delphi is an
established structured information gathering and
forecasting approach and has been used in a variety
of research topics, including within ecology and bio-
diversity conservation, for consulting global expert
opinion and judgements on the most important re -
search questions and topics (Sutherland et al. 2013,
Yates et al. 2018, Dey et al. 2020).
We first present the results of the most important re-
search questions as prioritised by academic scientists
(i.e. the authors of this work) and practitioners. These
questions are grouped under 9 interconnected research
themes. Next, we examine agreement in the research
priorities perceived by academic scientists and practi-
tioners to help determine where seascape ecology
may have the greatest impact as a solution-focussed
science. For each theme, we highlight key research
challenges followed by discussion of the potential for
seascape ecology to offer science that helps address
the challenges of each theme. We suggest that these
results may serve as a roadmap for applying seascape
ecology for the UN Decade of Ocean Science for Sus-
tainable Development (2021− 2030). The results and
discussion serve to inform an applied research agenda
for seascape ecology and to highlight the broad scope
of this emerging interdisciplinary science.
2. MATERIALS AND METHODS
2.1. Modified Delphi methodology
The coordination team (S. Pittman, K. Yates, and P.
Bouchet) adapted a 2-stage modified Delphi survey
methodology (Yates et al. 2018) conducted in 3 steps
to first (Stage 1) solicit research questions and then
prioritise research questions (Stage 2) through a 2-
step selection process (Fig. 2).
The 3 key steps were as follows. Step 1: A maxi-
mum of 5 research questions were solicited from aca-
demic scientists (including the coordinators) working
at the forefront of seascape ecology along with a brief
written rationale. Step 2: Academic scientists and
practitioners selected all important questions from a
curated list of the original questions grouped under 9
themes. Step 3: Academic scientists and practitioners
selected their 10 most important questions from those
they selected in Step 2.
Participants were asked to address the following
when proposing research questions (see invitational
letters in Text S1 in the Supplement at www. int-res.
com/ articles/ suppl/ m663 p001 _ supp .pdf):
(1) Questions must be of broad geographical rele-
vance, but can be focussed on any scale, with the
condition that the question relates to measurable
spatial patterns, patterning processes, or pattern−
process relationships.
Fig. 2. Modified Delphi approach used for prioritising applied seascape ecology research questions. Both academic scientists
and marine management/conservation practitioners were included in the consultative process

Pittman et al.: Priority research for seascape ecology 5
(2) Questions must address a knowledge gap that
will advance the practice of marine management,
conservation, and marine spatial planning if ade-
quately addressed within a decade.
2.1.1. Selection of participants
Academic scientists. We identified and in vited 50
academic scientists based on their research interests in
the application of landscape ecology concepts and
tools to the marine environment, as evidenced through
publications. Invitees included some of the coordinators’
previous research collaborators. We also encouraged
in vitees to suggest suitable colleagues (i.e. referral sam-
pling). Specialised ecological knowledge among the
academics included fish and fisheries, seabirds, biolog-
ical oceanography, eco informatics, re mote sensing and
habitat mapping, coral reef ecosystems, and saltmarsh
and seagrass ecology, with re search being conducted
across a wide range of focal scales and geographical
locations in temperate and tropical ecoregions.
Practitioners. We identified and invited 105 prac-
titioners who were primarily senior staff at inter-
governmental, governmental (national and local), or
non- governmental organisations, and specialist mar-
ine management consultants. The key objective was
to invite practitioners working in agencies that were
likely to have a use for the knowledge emerging from
seascape ecology. In the event of major gaps not ad -
dressed by the academics’ research questions, co -
ordinators invited practitioners to submit additional
questions of their own. No additional questions were
received.
The designation of respondents to a respondent
group (i.e. academic scientist or practitioner) was
based on the institution of employment at the time of
completing the survey. Practitioner respondents were
offered anonymity.
2.1.2. Prioritisation survey
The survey was designed using a professional
online platform (Qualtrics™, Snow & Mann 2013) to
frame the task, assess the level of expertise, present
the research questions, and quantify the survey re -
sults. This structured approach was designed to
reduce known cognitive and methodological bias
(Hallowell & Gambatese 2010) and minimise the time
required for participation. To reduce bias, the online
questionnaire was delivered with each theme, and
all questions within them, presented in random order.
Randomisation of the question order is an effective
method for eliminating primacy and contrast biases.
The contributor of each question re mained anony-
mous to all participants other than the coordinators.
Respondents were asked to self-assess their familiar-
ity with seascape ecology on a discrete scale ranging
from 1 (no knowledge) to 5 (expert), in half-point in -
crements. The survey then proceeded in 2 steps of
online voting. First (Step 2), respondents selected as
many important questions from the curated list as they
felt relevant to the task. Following this, respondents
were presented with their selected questions and
asked to identify from the shortlist the 10 most impor-
tant questions. The final set of top-priority questions
was identified based on the total number of votes
each question received across all respondents.
2.2. Data analysis
To quantify and rank priority research questions,
we calculated the proportion of all respondents in
each of the 2 groups (academics and practitioners) that
selected each question at Step 2 and Step 3. For the
results of Step 3, only the proportion of votes received
for each question selected was used to group ques-
tions into 3 priority classes using upper, middle, and
lower terciles, whereby highest priorities are ques-
tions with the upper tercile percentage scores (i.e. the
upper third of the data values). To avoid potential
bias, the respondents were not aware of the coordina-
tors’ intention to classify the re sponses into 3 priority
classes and had no knowledge of the intention to com-
pare academic scientist priorities with practitioner
priorities. Zeros were noted where a question was not
selected. Cross-comparison of priority classes was con -
ducted using a confusion matrix to evaluate the agree-
ment between academics and practitioners. An un-
paired Mann- Whitney test was used to determine if
self-assessed familiarity with seascape ecology was
significantly different between the 2 respondent groups.
3. RESULTS AND DISCUSSION
3.1. Respondents’ self-assessed knowledge of
seascape ecology
Of the 50 academic scientists contacted, 35 ac -
cepted the invitation to participate and submitted
applied research questions and then fully completed
the prioritisation questionnaire. Academics were affil-
iated with research institutions located in 9 countries

Mar Ecol Prog Ser 663: 1–29, 2021
(across 3 continents), with many having a global
scope of work. Forty of 105 practitioners contacted
engaged with the online questionnaire, resulting in
31 full completions and 9 incomplete questionnaires
that could not be used in this analysis. Practitioners
were based in 11 countries (across 4 continents), with
many having a global scope of work. Most (91%)
academic scientist respondents had a moderate to
high (score 3.5−5) level of self-assessed knowledge
of seascape ecology, while 52% of practitioners had a
moderate to high (score 3.5−5) knowledge of sea-
scape ecology (Fig. 3). Six practitioners had low
familiarity (score 1−2) with seascape ecology. The aca-
demic scientist population had a significantly higher
(4.2 ± 0.7 SD) self-assessed knowledge of seascape
ecology than the practitioner population (3.2 ± 1.2 SD)
(p < 0.001). All completed questionnaires were in -
cluded in the analyses. The lower familiarity with
seascape ecology among practitioner respondents
presents a key challenge to the transmission of re -
sults from seascape ecology into practice. Improving
awareness of seascape ecology, however, can be
addressed through co-design of demonstration pro-
jects, toolkits, training courses, meetings, and targeted
communications (Norström et al. 2020).
3.2. Curation of research questions
A total of 139 research questions were submitted.
Eleven questions that related to common challenges
across the applied sciences (e.g. political gover-
nance, data management) were considered too broad
to warrant inclusion. The remaining 128 research
questions were assessed by the expert coordination
team for redundancy. Repetition was removed by
consolidating questions, with care to avoid any sig-
nificant loss of key information from the original sub-
missions, resulting in a curated set of 55 questions.
Each question was assigned to 1 of 9 research themes
based on the primary content of each question.
Themes were defined as: seascape change; seascape
connectivity; restoration and sustainability science;
EBM; seascape mapping, modelling, and sampling
design; spatial and temporal scale; seascape goods
and services; pelagic seascapes; and emerging tech-
nologies and metrics (Table 1). Some questions were
relevant to multiple themes but were placed in a sin-
gle theme for analysis. The largest grouping of ques-
tions occurred under the following 3 themes: (1) sea-
scape change (11 questions); (2) seascape connectivity
(10 questions); and (3) EBM (10 questions) (Table 1).
The highest overlap in the content of the originally
submitted questions occurred within the theme ‘resto-
ration and sustainability science’, where 18 questions
exhibiting considerable overlap were consolidated
into 4 distinct questions. No additional re search ques-
tions were received from practitioners.
3.3. Relative importance among the 55 research
questions
From the 55 research questions presented to re-
spondents in the questionnaire (Step 2, Fig. 2), the ac-
ademic scientists selected an average of 32.4 ± 9.4 (SD)
and practitioners selected an average of 34.1 ± 9.2
questions as being important to advance the practice
of marine management, conservation, and spatial plan-
ning. The research themes ‘spatial and temporal scale’
and ‘emerging technologies and metrics’ were con-
sidered most important as priority research themes by
both academic and practitioner respondents (Fig. 4).
3.4. Highest-priority research questions
The sum of the votes from academic scientists
resulted in several of the 10 most important questions
receiving equal ranking, thereby placing a total of
22 research questions within the top 10 priorities
(Table 2). An additional 12 questions were selected
6
0
10
20
30
40
50
60
1 to 2 2.5 to 3 3.5 to 4 4.5 to 5
)%
(
s
t
ne
d
n
o
pse
r
fo no
i
tr
opo
r
P
Self-
assessed knowledge of seascape ecology
Academic scientists
Practitioners
Expert knowledge
Low familiarity
Fig. 3. Self-assessed knowledge of seascape ecology for all
respondents from the academic (n = 35) and practitioner (n =
31) sample groups. The discrete scale (0.5 increments)
ranged from 1 for low familiarity of seascape ecology to 5
with expert knowledge. Intervals shown here are inclusive

Pittman et al.: Priority research for seascape ecology 7
Research Number of Number of
theme questions questions
submitted post-curation
1. Seascape change 29 11
Dynamic spatial patterns and the ecological and social consequences of structural change
2. Seascape connectivity 24 10
Movement of living and non-living material from one location to another and the ecological
and social consequences; human attachment and interactions with the ocean
3. Restoration and sustainability science 18 4
Holistic spatial frameworks and systems science to inform human actions to address the
challenges of sustainability
4. Ecosystem-based management 16 10
Ecological systems approach to management including spatial management strategies
5. Seascape mapping, modelling, sampling 11 8
Spatially explicit pattern-oriented and multi-scale analytical methods and tools
6. Spatial and temporal scale 10 3
Scale selection, scale effects, and multi-scale frameworks
7. Seascape goods and services 9 3
Spatial patterns and ecological processes underpinning ecosystem services with a focus on
spatial context, configuration, and connectivity
8. Pelagic seascapes 72
Dynamic spatial patterns and ecological processes in the open ocean and the linkages to
benthic ecology
9. Emerging technologies and metrics 4 4
Spatial ecoinformatics, geospatial technologies, and advanced computing including
artificial intelligence
Total 128 55
Table 1. Results of the curation process to reduce redundancy in content across all research questions grouped within 9
research themes
0 102030405060708090100
Spatial & temporal scale
Emerging technologies & metrics
Ecosystem-based management
Seascape change
Seascape goods & services
Seascape mapping, modelling, sampling
Restoration & sustainability science
Pelagic seascapes
Seascape connectivity
Mean (+SE) percentage of respondents
Academic scientists
Practitioners
Fig. 4. Important research themes from Step 2 of the prioritisation process (see Fig. 2), presented as the proportion of academic
scientists (n = 35) and practitioner (n = 31) respondents who selected research questions in each of the 9 research themes. Mean
(+SE) calculated across all questions within a theme and plotted in descending order using the data from academic scientists

Mar Ecol Prog Ser 663: 1–29, 2021
8
Priority tier Research themes and questions
Academics Practitioners
1. Seascape change
1 2 Q3. What are the consequences of climate change (i.e. sea-level rise, changes to oceanographic conditions, and primary productivity) on seascape structure and function?
1 2 Q8. How can seascape ecology contribute to understanding the impacts of processes such as fragmentation and habitat loss on resilience and the identification of
spatial pattern-dependent tipping points?
2 3 Q22. How do range extensions or contractions of habitat-forming species alter seascapes and their function?
1 1 Q13. How can seascape ecology help set ecologically meaningful goals and targets for management in a changing ocean?
3 1 Q35. How can seascape ecology be used to better understand anthropogenic impacts (including cumulative impacts and synergistic effects) in the sea and at the
land−sea interface?
3 2 Q36. How can seascape ecology inform ecological risk assessments of anthropogenic impacts (e.g. climate change)?
3 2 Q46. How will climate change and other anthropogenic impacts that influence landscape conditions impact coastal seascapes?
2. Seascape connectivity
1 1 Q4. In which seascapes, and over which scales, do connectivity effects most improve the impact of management actions, and what connections are most critical for
ecosystem function, biodiversity, and ecosystem services (e.g. provisioning, regulating, supporting)?
1 3 Q12. How does connectivity modify the resistance to disturbance and recovery of ecological entities (from populations to ecosystems)?
1 3 Q14. How do different seascapes contribute to patterns of dispersal for species expanding their range (e.g. invasive, re-locations, climate shifting, recovering populations)?
2 1 Q15. How can seascape ecology be used to prioritise efforts to manage (enhance; maintain; mitigate) connectivity?
2 2 Q17. Where do species of conservation concern aggregate, what corridors exist among areas of high use, and are these influenced by the presence or absence of
conservation measures over time?
3. Restoration and sustainability science
1 1 Q5. How can seascape ecology inform the design and assessment of seascape restoration and creation efforts to improve success?
2 1 Q29. How can we best integrate a holistic systems approach into seascape ecology to serve as a sustainability science for the ocean?
4. Ecosystem-based management
1 1 Q1. How can seascape ecology be applied to inform conservation prioritisation and the design of spatial management strategies (e.g. marine protected area [MPA]
networks, dynamic MPAs, land−sea corridors, spatial action mapping, spatial planning)?
2 2 Q16. How can seascape connectivity be integrated into marine spatial planning?
2 3 Q18. How can seascape ecology contribute to fisheries management by considering spatial variability in pelagic seascapes?
2 1 Q23. What attributes of seascape patterns can be used to provide metrics or indicators to determine ecosystem health?
2 1 Q28. How can seascape ecology be applied to support the monitoring and assessment of management actions to evaluate their effectiveness?
2 2 Q31. How can seascape ecology enhance ecosystem-based management in the open oceans?
3 2 Q38. How do the effects of seascape context and connectivity modify conservation outcomes, and over what scales for which species and ecosystems?
3 2 Q41. What are the needs of coastal managers to increase their capacity to use a seascape approach?
5. Seascape mapping, modelling, and sampling design
1 2 Q10. How can seascape ecology be used to improve ecological modelling for predicting the geographical distribution of biota?
3 1 Q48. How much structural detail do we need to include when making habitat maps to detect and explain ecologically meaningful spatial patterns?
6. Spatial and temporal scale
2 2 Q19. What are the appropriate spatial and temporal scales for assessments of seascape resilience?
1 1 Q2. How should seascape ecology identify the relevant spatial and temporal scales over which patterns and processes are linked to inform management practices?
1 2 Q11. How can the multi-scaled approach often applied in seascape ecology assist in scaling solution-oriented marine management approaches relevant to local,
state, national, and international levels of coastal management and policy?
7. Seascape goods and services
1 1 Q9. Which seascape types provide maximum benefits in terms of biodiversity and productivity, and support optimal functional connectivity, and how will these
functions change through re-structuring processes resulting in habitat loss and fragmentation?
2 2 Q21. How do seascape patterns influence the flow and quality of ecosystem goods and the estimation of value and risk in natural capital assessments?
3 1 Q45. What methods are most effective for linking spatial characteristics of the seascape to social, cultural, and ecosystem service values that are meaningful to
management practitioners and communities?
8. Pelagic seascapes
2 2 Q20. What combination of survey and analytical techniques are most appropriate for characterising pelagic seascapes?
9. Emerging technologies and metrics
1 1 Q6. What are the most useful metrics and indicators for characterising and monitoring spatio-temporal patterns in seascapes, and over what scales should these be
measured?
1 2 Q7. How can seascape metrics be applied to help link spatial patterns to ecosystem function (e.g. understanding and modelling the responses of mobile animals to
physical conditions)?
2 1 Q24. How can we use emerging sensor technologies and data integration techniques to improve seascape mapping?
Table 2. Most important research questions selected (Step 3; see Fig. 2) by both academic scientists and practitioners, for a total of 34 questions across 9 themes. The
proportion of votes received was used to classify priorities into upper (≥ 24%, blue), middle (11−23%, grey), and lower (>11 %, light blue) terciles with the upper tercile
class being the highest-priority tier of research questions (n = 22 questions). Questions are grouped by theme and not in order of priority. The question identifier
uses numbering ordered in rank according to academic scientist votes (i.e. Q2 received more votes than Q22)

Pittman et al.: Priority research for seascape ecology
only by practitioners in Step 3, resulting in a total of
34 most important questions selected across both
respondent groups. The grouping of all 55 questions
into terciles based on Step 3 selections resulted in
the following tercile categories: higher (upper tercile
≥24%), medium (11.7−23%), and lower (≤11%) pri-
orities (Table 2; see Table S2). Questions 1, 2, and 3
were selected as important by 91, 94, and 71% of the
academic scientists, respectively, in Step 2 (Table S1)
and as being amongst the 10 most important ques-
tions selected in Step 3 by more than 40% of aca-
demic scientists (Table 2; Table S2). Practitioners
agreed that Q1 and Q2 were important in Step 2,
receiving 84 and 77% of the votes, and a high prior-
ity in Step 3 (39 and 32%) (Table S2). Q3 was impor-
tant to 65% of practitioners in Step 2 and ranked
tenth of 55 questions in Step 3. Combining the pro-
portion of votes from Step 3 selections from both
respondent groups ranked Q1, Q6, and Q5 as the 3
highest-priority research questions from Step 3.
3.5. Agreement on the ten most important
research questions
Comparisons of the votes for the 10 most important
research questions across all 55 questions (Table 2;
Table S2) suggested that practitioners and academic
scientists expressed highest agreement (59%) on the
lowest-priority questions, 50% agreement on the
highest priorities, and lower agreement on medium
(32%) priority questions (Table 3). The average differ-
ence in the proportion of votes received by each re-
spondent group (across all 55 questions) was 9 ± 7.5 %.
Across all 3 priority tiers, 36 of the 55 questions were
within a ±10 % band of agreement. Most notable dis-
agreement on priorities was that 2 of the high-priority
questions (Q12 and Q14) voted by academic scientists
were classified as the lowest-priority tier by practi-
tioners, and 3 of the lowest-priority questions for aca-
demic scientists (Q28, Q45, and Q48) were in the
highest-priority tier for practitioners (Fig. 5). Overall,
the highest disagreement occurred in the academic
scientists’ medium-priority tier, where 8 of 19 ques-
tions were in the lowest-priority tier for practitioners.
Five of the high-priority academic scientist’ questions
(Q3, Q7, Q8, Q10, and Q11) were medium-tier priori-
ties for practitioners. Two low-priority questions for
academics received zero votes in the practitioners’ top
10 research questions (Table S2).
Similar patterns of priorities between academics
and practitioners have been reported elsewhere (Cvi-
tanovic et al. 2013). For instance, the highest-ranking
(52% of the vote) question (Q6) in the prac titioners’
top 10 was ranked fifth by academic scientists and fo-
cussed on identifying and applying useful metrics and
indicators to characterise and monitor spatio-temporal
seascape patterns. The greatest between-group dif-
ference, 28% higher for practitioners than academic
scientists, was for Q28 on support for monitoring and
assessment of the effectiveness of management ac-
tions. Question 22 on the impact of species range ex-
tensions and contractions on seascapes was a very
low-priority question for practitioners but an upper
medium-tier priority for academic scientists. Although
many questions received same-tier agreement by
both groups (26 of 55 questions) (Table 3), the diverg-
ing priorities represent an important difference in pri-
ority setting. This misalignment reflects the greater
emphasis for practitioners on the need for science to
support ad vances in monitoring and assessment, in-
cluding metrics and indicators, and the need for a
more holistic socioecological science that is better
aligned with practice and policy (Dey et al. 2020). In
the theme of EBM, 8 of the 10 questions were selected
by practitioners in their 10 most important questions
compared with 3 selected by academic scientists. In
addition, practitioners prioritised addressing human
impacts on the marine environment as a higher prior-
ity than research questions that focussed on marine
organisms. For instance, Q35 on understanding hu-
man impacts in the sea and at the land−sea interface
was placed in the highest-priority tier by practitioners
and the lowest-priority tier by academic scientists.
Two of the research questions provided by academic
scientists (Q50 and Q51) that focussed on metapopu-
lations and teleconnections received zero selections
9
Academic scientists
Priority Highest Medium Lowest Total
Practitioners
Highest 7 5 3 15
(50%) (26%) (14 %)
Medium 5 6 6 17
(36%) (32%) (27 %)
Lowest 2 8 13 23
(14%) (42%) (59 %)
Total 14 19 22 55
Table 3. Confusion matrix showing the proportion of all 55
research questions classified into each priority class (highest
[blue], medium [grey], and lowest tercile [light blue]) based
on the proportion of votes received by academic scientists
and practitioners. The diagonal shaded boxes show the pro-
portion of agreement between respondent groups for each
priority class

Mar Ecol Prog Ser 663: 1–29, 2021
in the practitioners’ top 10 and very few (6%) selec-
tions by academic scientists. Despite receiving in-
creasing interest from landscape ecologists (Liu 2017,
Raya Rey & Huettmann 2020), re search on distant tele-
connections is often focussed on highly mobile species
and pattern−process relationships across multi-decadal
timescales and spatial scales far broader (i.e. ocean
basin, spanning hemispheres) than is typical in sea-
scape ecology. Al though congruence between aca-
demic scientists and practitioners was mixed across
the 3 priority tiers, the importance of seascape ecology
research to practitioners was emphasised by agreement
on 12 of the 22 top-ranked questions, including the
agreement on 5 of the 6 highest-ranking questions.
Among the places of disagreement, question 45
(‘What methods are most effective for linking spatial
characteristics of the seascape to social, cultural, and
ecosystem service values that are meaningful to man-
agement practitioners and communities?’) was ranked
in the highest-priority tier by practitioners and lowest-
priority tier by academics. This apparent disconnect
between science and practice reflects an expected
disparity between seascape ecologists who primarily
focus on marine organismal ecology and practitioners
who are more likely to focus on complex socioeco-
nomic, political, and cultural issues linked to marine
management. To some extent, voting choices may be
biased by individual experience, interests, pressing
environmental policy, current trends in topics, per-
ceived barriers to progress, and the phrasing and fa-
miliarity of questions that may infer either a more
solution-focussed or more basic science-focussed prob-
lem (Drescher et al. 2013). Furthermore, we acknowl-
edge that the design of surveys, including the way
tasks are presented for expert judgement, will have
an associated cognitive bias that is method dependent.
Differences emerging from the 2 respondent groups
may also be the result of the demonstrated lower
awareness of seascape ecology in the practitioner
group. However, the major differences, as expected,
are more likely reflective of the greater importance to
practitioners of reliable tools and information to help
prioritisation, implementation, and effectiveness of
actions. A lthough not discussed here, we acknowl-
edge that many cultural drivers will have a bearing on
the application of seascape ecology to practice, in-
cluding global governance, political and economic
systems, knowledge exchange, and data access.
3.6. How seascape ecology can help address
applied research challenges
For each research theme, we list here only the sin-
gle highest-ranked research question resulting from
the votes from each respondent group. All others are
10
Fig. 5. Proportion of votes by question for the 10 most important research questions (Step 3 of prioritisation; see Fig. 2) cast by
academic scientist and practitioner respondent groups. The 10 questions with the greatest disparity between respondent
groups are numbered and identified using red arrows. Upper tercile questions (blue) represent the highest priority, and lower
tercile questions (light blue) represent the lowest priority

Pittman et al.: Priority research for seascape ecology
provided in Table 2 (and Tables S1 & S2). To contex-
tualise all questions within each research theme, we
provide a broad synthesis of key research challenges
and a horizon scan exploring the potential for sea-
scape ecology to address these challenges.
3.6.1. Theme 1: Seascape change
The highest-priority research question in the
theme of seascape change was Q3, ranked third by
academic scientists and tenth by practitioners. For
practitioners, Q13 was the highest priority (ranked
sixth) and ranked eighth by academic scientists.
Q3: What are the consequences of climate change
(i.e. sea-level rise, changes to oceanographic condi-
tions, and primary productivity) on seascape struc-
ture and function?
Q13: How can seascape ecology help set ecologi-
cally meaningful goals and targets for management
in a changing ocean?
Research challenges. Despite recognition that spa-
tial patterns can be used to investigate change and
predict resilience (Levin 1992, Kelly et al. 2011,
Kavanaugh et al. 2016), the spatially explicit patterns
of seascape change are often overlooked, hindering
our ability to anticipate and mitigate the adverse
consequences of structural change. For instance, the
composition and spatial configuration of coastal sea-
scapes is being changed by accelerated climate
change and other human impacts (e.g. loss, expan-
sion and fragmentation of seagrass beds, kelp beds,
saltmarshes, and mangroves) (Halpern et al. 2019).
Across the global tropics, remote sensing data from
air- and space-borne sensors have revealed the com-
plex spatial and temporal patterns in the biological
responses of corals to marine heat waves (Page et al.
2019). Such complex changes emerging at multiple
scales justify the application of pattern-oriented sci-
entific methods in attempts to understand and pre-
dict the consequences of changing seascape struc-
ture on ecological functions (Wu 2019, Bryan-Brown
et al. 2020) and to identify spatial threshold effects
(Yeager et al. 2016, Santos et al. 2018). Bridging sci-
ence and practice for a better understanding of change
will require innovative and integrative spatial frame-
works with pattern-oriented indicators to inform spa-
tial planning, restoration design, and ecosystem-
based climate adaptation strategies (Babí Almenar et
al. 2018, Paulo et al. 2019).
Application. Seascape ecology recognises that
environmental change plays out as a pattern-form-
ing ecological process operating across multiple
scales (Levin 1992). The application of concepts,
spatial models, and spatial pattern metrics from
landscape ecology has been transformative in
understanding coastal ecosystem dynamics at spa-
tial scales that are operationally relevant to man-
agement decision making (Browder et al. 1985,
Costanza et al. 1990, Hovel & Regan 2008, Santos et
al. 2018). Advances in computation are continually
improving efforts to incorporate more complex pat-
terns and processes into modelling at finer resolu-
tions and across broader spatial and temporal
scales. Integrating behavioural responses to spatial
patterns into spatial models, such as in individual-
based models (Stillman et al. 2015, Hovel & Regan
2018), and increased performance of multi-scale
predictive mapping (Pittman & Brown 2011, Hattab
et al. 2014, McGarigal et al. 2016) will help reduce
uncertainty in our efforts to explain and forecast the
ecological consequences of seascape shifts under a
changing climate. For example, linking the patterns
of structural change in habitat to ecological pro-
cesses such as predator−prey dynamics and the
implications for food web structure can inform man-
agement decisions (Gilby et al. 2020b). For the open
ocean, the merging of hierarchy theory and patch
dynamics with oceanographic and ecological para-
digms provides an ecological framework with impli-
cations for advancing dynamic ocean management
for sustainable fisheries and biodiversity conserva-
tion (Hidalgo et al. 2016, Kavanaugh et al. 2016),
which will be a valuable management approach as
species’ ranges continue to shift. Predicting marine
species’ geographical range shifts in response to
ocean warming will benefit from greater integration
of interacting spatial factors (e.g. benthic seascape
configuration and connectivity) that will, for many
species, also affect habitat suitability, organism
movements, and capacity to adapt (McHenry et al.
2019, Cattano et al. 2020, Lauchlan & Nagelkerken
2020, Morley et al. 2020). Such complex challenges
will require ad vances in data integration and a sea-
scape ecology framework capable of adopting sys-
tems science concepts and techniques and the
capacity to integrate in formation from movement
ecology, oceanography, genomics, metapopulation
biology, and socio- economics (Fowler et al. 2013,
Liu et al. 2015, Lowerre-Barbieri et al. 2019). Infor-
mation on the interlinked spatial components of
seascapes will help to broaden the scale at which
structural and functional ecosystem integrity is
defined, with potential for creation of indices of sea-
scape condition that inform management goals and
actions in a changing climate.
11

Mar Ecol Prog Ser 663: 1–29, 2021
3.6.2. Theme 2: Seascape connectivity
The highest-priority research question in the theme
of seascape connectivity was Q4, ranked fourth by
academic scientists and sixth by practitioners. For
practitioners, Q15 was the highest priority (ranked
fifth) and ranked ninth by academic scientists.
Q4: In which seascapes, and over which scales, do
connectivity effects most improve the impact of man-
agement actions, and what connections are most crit-
ical for ecosystem function, biodiversity, and ecosys-
tem services (provisioning, regulating, supporting)?
Q15: How can seascape ecology be used to priori-
tise efforts to manage (enhance, maintain, mitigate)
connectivity?
Research challenges. In many locations, it re -
mains unclear how human activities have modified
the material flux between landscapes and sea-
scapes and disrupted life cycle connectivity and the
flow of ecosystem services from coastal ecosystems,
as well as how best to restore, create, and protect
ecological connectivity (Olds et al. 2016, Carr et
al. 2017, Balbar & Metaxas 2019). A key research
challenge is to determine the ecological functions
that are modulated by connectivity and identify the
spatial and temporal scale(s) over which these func-
tions enhance ecosystem services and conservation
outcomes (Olds et al. 2016, Weeks 2017, Theuer -
kauf et al. 2019). This also ex tends to often complex
interactions between distant places (telecoupling)
that can lead to unexpected outcomes with impor-
tant implications for sustainability (Liu et al. 2013,
Raya Rey & Huettmann 2020). Connectivity is also
an important process in the deep sea, where long-
term monitoring has re vealed mass fish migrations
synchronised with seasonal cycles of primary pro-
ductivity, connecting surface waters with the deep
(Milligan et al. 2020).
Globally, the maintenance and restoration of river−
sea and land−sea functional connectivity for the many
species that require unimpeded structural habitat
connectivity to close their life cycles is a pressing and
complex challenge (Beger et al. 2010). The socioeco-
nomic consequences of ecological connectivity are
receiving growing interest (Rees et al. 2018b, Popova
et al. 2019), yet we still know relatively little of the
linkages between ecological connectivity and provi-
sioning of ecosystem services (Barbier 2018). Efforts
are underway globally to synthesise and integrate
information on ecological connectivity for effective
spatial planning and global biodiversity conservation
with potential to advance the emerging ecological
concepts such as blue corridors, ecological networks,
and pelagic MPAs (Pittman et al. 2014, Schill et al.
2015, Dunn et al. 2019).
Application. Connectivity is a core concept in sea-
scape ecology. Seascape connectivity describes the
degree to which a seascape facilitates or hinders the
movement of organisms, or the flow of genetic mate-
rial, nutrients, and other matter (Grober-Dunsmore
et al. 2009). Seascape ecology can help advance the
integration of seascape connectivity into decision sup-
port tools and best practice principles that inform ac-
tions that maintain connectivity and rehabilitate dys-
functional connectivity (Watson et al. 2017, Walt ham
et al. 2019). Furthermore, better integration of sea-
scape structure and function into coupled biophysical
connectivity modelling will improve tools to predict
pathways and consequences of invasive species, pa-
thogens (Kough et al. 2015), and the spread of regime
shifts (Hughes et al. 2013) to inform mitigation and
adaptation strategies.
Specific connectivity metrics and software for mod-
elling actual, structural, and potential connectivity
have been created and applied to terrestrial land-
scapes, freshwater ecosystems (e.g. riverscapes), and
seascapes (Calabrese & Fagan 2004, Virtanen et al.
2020). Indirect estimations, or potential connectivity,
can be measured and modelled using probabilistic or
predictive spatial models of movement or habitat dis-
tributions (Lowe & Allendorf 2010, Treml et al. 2015,
Puckett & Eggleston 2016). Graph-theoretical meth-
ods, as used in landscape ecology, provide an ef -
fective tool to visualise complex patterns of spatial
connectivity at scales that are operationally relevant
to management with demonstrated contributions to
conservation planning (Treml & Halpin 2012, Saun-
ders et al. 2016). Neutral seascape models allow us
to test and explore through spatial simulations the
influence of simplified seascape configuration, hydro -
dynamics, and scale on organism space-use strate-
gies (Caldwell & Gergel 2013). Dynamic models of
potential connectivity, especially propagule disper-
sal, have received considerable attention in marine
systems regarding sources and sinks, marine meta -
populations (Kool et al. 2013, Treml et al. 2015, Puckett
& Eggleston 2016), and the design and performance of
MPA networks (Carr et al. 2017, Jonsson et al. 2020).
A wide variety of ecosystem services depend on
the movement of organisms and materials across sea-
scapes and between land and sea. For example, the
fisheries ecosystem service value can be influenced
by seascape connectivity of coastal marine ecosys-
tems, with well-documented examples including
interconnected nursery habitats referred to as ‘sea-
scape nurseries’ (Nagelkerken et al. 2015, Perry et al.
12

Pittman et al.: Priority research for seascape ecology
2018, Berkström et al. 2020). Identification of areas of
critical habitat and ecological connectivity for sus-
taining biodiversity and ecosystem services is in -
creasingly required for spatial conservation planning
(Mumby 2006, Weeks 2017, Yates et al. 2019, Proud-
foot et al. 2020).
Spatial pattern metrics quantifying benthic sea-
scape connectivity can help design protected areas
that maximise structural connectivity (Engelhard et
al. 2017, Weeks 2017, Proudfoot et al. 2020). Im -
proved functionality in spatial planning software
enables data on actual and potential ecological con-
nectivity to play a role in the design of conservation
measures such as protected area networks (Virtanen
et al. 2020). Increased sophistication in analytical
techniques for multi-dimensional and cross-scale
analyses of fluid processes will advance our capabil-
ity to understand and better manage vertical connec-
tivity (e.g. nutrient exchange) coupling benthic and
pelagic components (Griths et al. 2017). Seascape
ecology must also begin to include the multi-scale
spatial patterns and processes of the often over-
looked marine microbial communities. For example,
marine microbes play a crucial role in the vertical
transport of material and nutrient cycling, yet we
know little of the interconnectedness between micro-
scopic and macroscopic patterns and processes.
3.6.3. Theme 3: EBM
The highest-priority research question in the
theme of EBM was Q1, ranked first by academic sci-
entists and third by practitioners. For practitioners,
Q28 was the highest priority (ranked second) and
ranked 12th by academic scientists.
Q1: How can seascape ecology be applied to
inform conservation prioritisation and the design of
spatial management strategies (e.g. MPA networks,
dynamic MPAs, land−sea corridors, spatial action
mapping, spatial planning)?
Q28: How can seascape ecology be applied to sup-
port the monitoring and assessment of management
actions to evaluate their effectiveness?
Research challenges. Calls for more holistic and in-
clusive approaches to marine management and con-
servation that consider local ecological knowledge and
social justice (Bennett 2018) present important chal-
lenges for scientific research and for the evolution of a
sustainability science for the ocean. EBM is an inte-
grated approach to place-based management that
considers the entire ecosystem, including humans,
with the goal to ‘maintain an ecosystem in a healthy,
productive and resilient condition’ (McLeod et al.
2005, p. 1). The application of ecological principles,
including those from landscape ecology, have been
linked to the implementation of EBM, such as the de-
sign of MPAs, coherent MPA networks, and broader
marine spatial planning (Roberts et al. 2003, Crowder
& Norse 2008, Foley et al. 2010). For example, achiev-
ing qualitative elements of the Aichi Biodiversity Tar-
get 11 by 2020 re quired spatially explicit information
on the 4Cs of seascape ecology to design ‘ecologically
representative and well-connected systems of pro-
tected areas… integrated into the wider landscape
and seascape’ (Convention on Biological Diversity;
www. cbd.int/sp/targets/rationale/ target-11/). However,
those criteria are rarely achieved or assessed in prac-
tice (Rees et al. 2018a,b, Meehan et al. 2020).
Application. With a focus on multi-scale system
complexity, we suggest that seascape ecology pro-
vides an appropriate framework to enhance the con-
tribution of ecological science to both goal setting
and provisioning of evidence when addressing biodi-
versity conservation and sustainable development
goals. Concepts familiar to landscape and seascape
ecologists such as ecological connectivity, corridors,
ecological networks, scale-effects, and habitat frag-
mentation permeate marine conservation and spatial
planning through EBM (Crowder & Norse 2008).
Similarly, core concepts from landscape ecology in -
creasingly bridge the science−policy gap, playing a
central role in national and global policy for biodiver-
sity conservation, restoration, and sustainable devel-
opment (Choi et al. 2008, Opdam et al. 2018, Rees et
al. 2018a, Balbar & Metaxas 2019).
From an operational perspective, adaptive monitor-
ing will require spatial pattern metrics that re flect
function, including novel ocean-specific metrics capa-
ble of serving as condition indicators (e.g. frontal den-
sities, patchiness, and gradients in kinetic energy)
(Miller & Christodoulou 2014, Alvarez-Berastegui et
al. 2016). Spatial tools for systematic conservation
planning that assist in prioritising places for conserva-
tion action have been ecologically re fined with princi-
ples from landscape ecology (Beger et al. 2010,
Oleson et al. 2018). Development of pattern-oriented
adaptations of incisive systems approaches, such as
causal chain analysis (Qiu et al. 2018) and the Drivers−
Pressures−State Change− Impact−Response frame work
(Matta & Serra 2016), could facilitate the integration
of seascape patterns into holistic ecosystem assess-
ments (Dreujou et al. 2020). Although rarely identified
in seascapes, spatial leverage points where a small
shift in spatial configuration can produce large and
sometimes abrupt changes, could provide an effective
13

Mar Ecol Prog Ser 663: 1–29, 2021
tool for prioritising actions for mitigation of human im-
pacts and predicting spatial resilience. Progress in ad-
dressing all of the priority research questions across
all 9 cross-cutting themes will support the implemen-
tation of EBM.
3.6.4. Theme 4: Restoration and sustainability
science
The highest-priority research question in the
theme of restoration and sustainable development
was Q5, ranked fourth by academic scientists and
third by practitioners. Both groups voted with a high
agreement (40 and 39%, respectively).
Q5: How can seascape ecology inform the design
and assessment of seascape restoration and creation
efforts to improve success?
Research challenges. Our understanding of ecolog-
ical complexity has profound implications for the way
that we perceive the world, our place in it, and how
we design actions to restore ecosystems and achieve
sustainable development (Levin 1992, Wu 2013). To
help society address the many challenges of manag-
ing for sustainable seascapes, ecologists will need to
advance integrative and transdisciplinary approaches
to study socioecological systems (Opdam et al. 2018,
Pittman et al. 2018, Alexander et al. 2019). The need
for ecological science to support transition to an
alternative economic development model (e.g. steady-
state, degrowth) and the challenge to realise a ‘sustain-
able blue economy’ will rise in prominence with the
rapid growth and diversification of ocean and coastal
uses (Huettmann & Czech 2006, Jouray et al. 2020).
Linking spatial characteristics of the seascape to
functions, values, and metrics that are meaningful
to decision-makers will facilitate communication
and knowledge exchange among academic scien-
tists, management practitioners, industry, and com-
munity groups.
In 2019, the UN General Assembly declared
2021−2030 the ‘UN Decade on Ecosystem Restora-
tion’, calling for accelerated global action to restore
degraded ecosystems (Duarte et al. 2020). Restora-
tion of coastal seascapes, however, presents a com-
plex and often financially costly intervention with a
highly variable short-term performance for some
habitat types and locations (Bayraktarov et al. 2016,
van Katwijk et al. 2016), and measurable success for
others (e.g. seagrass beds in the USA: Rezek et al.
2019; kelp forests in Australia: Layton et al. 2020). A
global review of 89 coastal marine restoration pro-
jects revealed that only 13% considered landscape
context in site selection, yet of those that did, 60%
supported larger and more diverse animal popula-
tions than control areas (Gilby et al. 2018b). Spa-
tially explicit and ecology informed transdisciplinary
approaches stand to benefit habitat and seascape
restoration through optimal site selection, enhanced
ecological design, improved prediction of post-resto-
ration ecological trajectories, and addressing the
challenges of scaling up restoration efforts (Bell et al.
1997, Gilby et al. 2018b, Waltham et al. 2020).
Application. Seascape ecology has great potential
to support restorative and sustainability science
through a place-based, multi-scale, whole-system
understanding of the dynamic spatial relationships
among seascape structure, ecosystem services, and
human wellbeing (Cumming 2011, Wu 2013, Opdam
et al. 2018). We suggest that a scientific consideration
of how the 4Cs can influence the success of coastal
restoration strategies and help anticipate conse-
quences for neighbouring areas will advance sea-
scape restoration (Bell et al. 1997, Gilby et al. 2018a,
2020a). Although evidence for the importance of the
4Cs on the ecological performance of management
actions is increasing, in some settings these attrib-
utes are still not considered sufficiently at the design
stage in restoration projects (Simenstad et al. 2006,
Gilby et al. 2018b, Lester et al. 2020). Most coastal
restoration efforts focus on single habitat types (e.g.
seagrass, saltmarsh, oyster reef, mangrove), with site
selection typically omitting consideration of the spa-
tial configuration of restored sites and the patterns of
connectivity (Lester et al. 2020). A shift in perspective
from a single patch type to a patch mosaic, or sea-
scape type, promotes a more comprehensive consid-
eration of species connectivity, seascape configura-
tion, community-level processes, external threats,
feedback loops, ecosystem service flows, and con-
nectivity with the wider landscape and seascape.
Where restoration goals seek to optimise co-benefits
from restored seascapes (e.g. climate mitigation from
blue carbon, coastal protection, biodiversity, and
food security), a spatially explicit focus on the 4Cs
should inform strategies and expectations (Moberg &
Rönnbäck 2003, Simenstad et al. 2006, Barbier 2017,
Gilby et al. 2020a). Seascape ecology has the poten-
tial to provide spatial design principles for seascape
restoration based on the 4Cs.
Active restoration projects present excellent oppor-
tunities for field experiments on pattern−process
relationships (Ellison et al. 2020); however, it is spa-
tial modelling in landscape ecology that has been
more often used as a powerful and flexible tool to
evaluate site suitability, explore different spatial
14

Pittman et al.: Priority research for seascape ecology
design scenarios, and analyse trade-offs to guide
actions (Sleeman et al. 2005, Brudvig et al. 2017,
Lester et al. 2020). Although rarely examined, knowl-
edge of seascape configuration could provide infor-
mation to calculate habitat availability and carrying
capacity for recovering populations in response to
protection or habitat restoration, as well as to identify
spatial limitations and bottlenecks to recovery. In
addition to informing innovative seascape restoration
science, seascape ecologists will be effective knowl-
edge brokers in the evaluation of learning from
broad-scale terrestrial landscape restoration studies,
with potential benefit to scaling up the restoration of
coastal seascapes.
3.6.5. Theme 5: Seascape mapping, modelling, and
sampling design
The highest-priority research question in the theme
of seascape mapping, modelling, and sampling design
was Q10, ranked seventh by academic scientists and
ninth by practitioners. For practitioners, Q48 was the
highest priority (ranked sixth) and ranked 15th by aca-
demic scientists, highlighting a substantial (23%) di-
vergence of agreement between the 2 groups.
Q10: How can seascape ecology be used to im -
prove ecological modelling for predicting the geo-
graphical distribution of biota?
Q48: How much structural detail do we need to
include when making habitat maps to detect and
explain ecologically meaningful spatial patterns?
Research challenges. Determining which patterns
to measure and how to measure them remains a per-
vasive challenge in marine ecology and management
(Levin 1992, Capotondi et al. 2019). A significant out-
standing challenge lies in developing mapping tech-
niques that incorporate dynamic processes, includ-
ing sub-surface patterns (Brodie et al. 2018), to
facilitate the linking of structure and function. Geo -
spatial products such as benthic habitat maps and
maps of pelagic structure (e.g. ocean fronts) are
important spatial data that enable ecological analy-
ses and often form the foundational data layers for
the development of marine spatial planning and a
wide range of area-based sampling, monitoring, and
conservation actions (Cogan et al. 2009, Brown et al.
2011, Miller & Christodoulou 2014). Working with
maps in ecology presents a wide variety of method-
ological challenges associated with thematic and
spatial resolution, as well as temporal dynamics
(Lechner & Rhodes 2016). Mismatches between eco-
logical, observational, and analytical scales can
be problematic because they can bias species−
habitat relationships and constrain ecological ques-
tions (Brown et al. 2011, Lecours et al. 2015). Increas-
ingly, however, targeted research-led mapping has
focussed on capturing ecological patterns that specif-
ically consider species, communities, and biodiver-
sity elements of the seabed and water column (Colbo
et al. 2014, Costa et al. 2014, Lacharité & Brown
2019). Most habitat maps used in ecology are static
products representing snapshots of structure and
requiring repeat mapping over time to capture
meaningful ecological dynamics. This may only be
needed infrequently for relatively stable structures
(e.g. seafloor geology) or when tracking long-term
change (Santos et al. 2016). However, pelagic sea-
scapes require a dynamic geographic framework
with near-real-time mapping of fluid patterns and
processes to advance dynamic ocean management
(Maxwell et al. 2020). Predictive models suggest that
dynamic spatial management can improve risk man-
agement in fisheries and meet conservation objec-
tives in the face of changing ocean conditions (Hazen
et al. 2018, Welch et al. 2019). Maps and ecological
models of seascape patchiness, spatial gradients, and
scale effects also have an im portant role to play in
sampling design, particularly when assessing human
impacts and monitoring the effectiveness of manage-
ment actions (Hewitt et al. 2007, Sandel & Smith
2009). The potential for bias from inadequate consid-
eration of variability in the 4Cs has received little
attention in both landscape and seascape ecology,
yet has considerable implications for data acquisi-
tion, analyses, and interpretation.
Application. Seascape mapping enables the acqui-
sition of baseline information, the evaluation of EBM
strategies, and explorations of research questions
relevant to seascape ecology (Brown et al. 2011,
Wedding et al. 2011, Lecours et al. 2015). The pri-
mary use of seascape maps has been to quantify and
compare seascape patterns and pattern-forming pro-
cesses at a range of spatial and temporal scales and
to explore linkages between seascape patterns and
animal distributions (Boström et al. 2011, Staveley et
al. 2017, Lacharité & Brown 2019). Novel integration
of stable isotope data with remote sensing to map
species’ energetic re sources across seascapes is one
example of integrative seascape ecology thinking
that is advancing our pattern−process understanding
(James et al. preprint https://doi. org/10. 1101/ 2020. 08.
03. 234781). Seascape ecologists can be both makers
and end-users of maps, demonstrating technical
skills, knowledge of ecologically meaningful scales,
and understanding of the limitations and uncertain-
15

Mar Ecol Prog Ser 663: 1–29, 2021
ties at all stages of data collection, processing, analy-
sis, and interpretation (Wedding et al. 2011). Empha-
sis is placed on the choice of conceptual model for
representing seascape structure (patch matrix, patch
mosaic, gradient models; McGarigal et al. 2009),
understanding and quantifying the effects of the-
matic and spatial map resolution, map classification,
the scale of analyses, and any bias caused by the
propagation of spatial errors through the analytical
process (Kendall et al. 2011, Wedding et al. 2011,
Lecours et al. 2015, Lecours 2017). Adopting such
novel, multi-scale techniques from landscape ecol-
ogy has advanced spatial predictive modelling, with
examples from shallow tropical waters (Pittman et al.
2007, Purkis et al. 2008, Wedding et al. 2008, Sta-
moulis et al. 2018), temperate waters (Pittman &
Costa 2010), Arctic waters (Huettmann et al. 2011,
Misiuk et al. 2018), deep-sea environments (Ross &
Howell 2013), and the global ocean (Wei et al. 2010).
Application of machine-learning algorithms that
allow interactions between predictor variables across
multiple spatial scales have enabled seascape het-
erogeneity to be better considered, leading to new
hypotheses on ecological responses and boosted
model performance (Huett mann & Diamond 2006,
Pittman & Brown 2011, Humphries et al. 2018,
Lacharité & Brown 2019). Future technological ad -
vances will likely see these predictive mapping tech-
niques applied to 3- and 4-dimensional seascapes
through multidimensional data cubes, with potential
to play a valuable role in ecology and marine spatial
planning, such as modelling water column structure
or organism movement pathways (Tracey et al. 2014,
Papastamatiou et al. 2018, Demšar & Long 2019,
Melo-Merino et al. 2020) and predicting 4-dimen-
sional shifts in species distributions due to global
warming.
A growing body of evidence also suggests that the
4Cs influence seascape function. These variables
must therefore be considered in sampling designs,
especially when selecting impact and control sites
(e.g. when comparing performance between unpro-
tected and protected areas; Huntington et al. 2010,
Olds et al. 2012, Rees et al. 2018). Sub-optimal sam-
pling designs could result from the lack of considera-
tion of the 4Cs, with potential to bias results in com-
parative studies leading to erroneous conclusions on
the effectiveness of management actions. Where
benthic maps are available, seascape ecology can
help recognise context-dependency (Bradley et al.
2020) and can facilitate re-analyses of historical data
with inclusion of seascape patterns and shift focus to
habitat mosaics, or ‘seascape types’ (sensu Pittman et
al. 2007) instead of single habitat types (Pasher et al.
2013, Bradley et al. 2020). Although few examples
exist, spatially explicit simulation modelling can be
used to optimise sampling designs that account for
seascape patterns, processes, and scale (Albert et al.
2010, Zurell et al. 2010, Hovel & Regan 2018).
3.6.6. Theme 6: Spatial and temporal scale
The highest-priority research question in the
theme of spatial and temporal scale was Q2, ranked
second by academic scientists and fifth by practition-
ers. Both groups voted this question into the highest-
priority tier (46 and 32%, respectively).
Q2: How should seascape ecology identify the rel-
evant spatial and temporal scales over which pat-
terns and processes are linked to inform manage-
ment practices?
Research challenges. Scale is fundamental to all of
ecology and presents a unifying challenge for aca-
demic scientists and practitioners that pervades
many, if not all, applications of ecological science
to management practice and policy (Levin 1992,
Schneider 2001, Cumming et al. 2006, Guerrero et
al. 2013). Inadequate accounting of scale and inap-
propriate scale selection can result in inflated un -
certainty, incomplete interpretation of cause−effect
relationships, and, at worse, can mislead decision
making (Meentemeyer 1989, Cumming et al. 2006).
The scale of observation can have profound conse-
quences for the interpretation of results, with differ-
ent patterns emerging at different scales of in -
vestigation (Huettmann & Diamond 2006, Schneider
2009, Pittman & Brown 2011, Fernandez et al. 2017).
For instance, species−environment associations can
change from strongly positive to strongly negative
with a change in the scale of analysis (Wiens et al.
1987, Huettmann & Diamond 2006). Cross-scale
analyses of predator−prey interactions in pelagic
seascapes suggest that physiological and ecological
parameters vary according to spatial and temporal
scales and can be closely coupled (Steele 1989), yet
cross-scale interactions can often increase uncer-
tainty in EBM (Glaser & Glaeser 2014). The appropri-
ate selection of temporal scales also presents a
research challenge that has been made more urgent
by accelerated seascape change where mismatches
in the temporal scale of dynamic phenomena (e.g.
non-stationarity, evolution, asynchronous behaviour,
shifts in scheduling) can undermine the identifica-
tion of causative variables and impede the applica-
tion of science to practice (Wolkovich et al. 2014).
16

Pittman et al.: Priority research for seascape ecology
Although rarely executed sufficiently in conven-
tional marine ecology, the explicit consideration of
scale is necessary at every step of the research pro-
cess, from the framing of hypotheses to the collection
of data, the design of field experiments and from
analyses to interpretation and application (Schneider
2009, Wedding et al. 2011, Lecours et al. 2015).
Application. A preoccupation with scale, especially
spatial scale, is a defining trait of landscape and sea-
scape ecology and has resulted in significant ad -
vancement in our conceptualisation and method-
ological consideration of scale and scaling (Wiens
1989). Unsurprisingly, many of the research ques-
tions formulated by academic scientists, such as pre-
sented here, acknowledge the importance of scale.
Explicit consideration of scale effects, the recognition
of multi-scale drivers, cross-scale coupling, and
scale-dependency offers great promise for advancing
effective management actions. At the organism level,
species, and individuals within them, can respond
to environmental heterogeneity in contrasting ways
and at different scales (Kotliar & Wiens 1990,
McGarigal et al. 2016). If we accept this organism-
centric or process-focussed view in seascape ecology,
then our framing of research questions and design of
methodology, particularly scale selection, must be
anchored to scales that are ecologically meaningful
to the focal organism, community, or process. Often,
a focal scale can be defined by an ecological process
such as an organism’s movement patterns (Wiens &
Milne 1989, Pittman & McAlpine 2003). For practical
purposes, a spatial continuum of complex patterns is
often handled through the concept of spatial hierar-
chies with multiple focal levels (Kotliar & Wiens
1990). Like landscape ecology, seascape ecology
contends with large and diverse datasets across a
wide array of spatial and temporal scales and can
integrate information derived from reductionist and
holistic science.
Scale awareness and seascape ecology thinking
have direct implications for the design of multi-scale
spatial management solutions that facilitate cross-
scale management and minimise scale mismatches
(Lagabrielle et al. 2018).
3.6.7. Theme 7: Seascape goods and services
The highest-priority research question in the
theme of seascape goods and services was Q9,
ranked seventh by academic scientists and sixth by
practitioners. This question received an equal pro-
portion of votes (29%) by both groups. Q45 was the
highest priority for practitioners (ranked fifth), but it
was only ranked 15th by academic scientists, high-
lighting a substantial divergence of agreement be -
tween the 2 groups for this question.
Q9: Which seascape types provide maximum ben-
efits in terms of biodiversity and productivity, sup-
port optimal functional connectivity, and how will
these functions change through re-structuring pro-
cesses resulting in habitat loss and fragmentation?
Q45: What methods are most effective for
linking spatial characteristics of the seascape to
social, cultural, and ecosystem service values that
are meaningful to management practitioners and
communities?
Research challenges. Understanding how seascape
structure, composition, and spatial configuration
affect the quality, productivity, and rate of flow and
delivery of ecosystem services is critical for natural
capital accounting and designing restorative and
sustainable development strategies. For example, in
tropical coastal areas, recognition of synergistic
interactions among adjacent patches of mangrove,
seagrass, and coral reefs has led to a conceptual shift
from a single patch to patch mosaics in the character-
isation of ecosystem services (Moberg & Folke 1999,
Moberg & Rönnbäck 2003, Harborne et al. 2006).
This approach acknowledges that the whole inter-
connected system contributes to ecosystem services
(Fig. 6), such that the combined spatial configuration
of coral reefs, seagrass, and mangroves enhances
coastal protection from waves and storms whilst also
influencing coastal resilience (Guannel et al. 2016).
Likewise, horizontal and vertical connectivity and
structural heterogeneity mediate the flow of ecosys-
tem services in the deep sea (Townsend et al. 2018,
Turner et al. 2019), and sea surface productivity
fronts have been considered to form ‘hotspots of
ecosystem services’ in the pelagic ocean (Martinetto
et al. 2020). Economic models have also begun to
consider the influence of seascape configuration on
ecosystem services and the cost−benefits associated
with human modifications to the configuration
(Sanchirico & Springborn 2011, Barbier & Lee 2014).
Mapping of ecosystem service rarely considers the
4Cs, yet this new ‘seascape economics’ perspective,
with a focus on how goods and services are gener-
ated through ecological connectivity, has the
potential to transform marine natural capital ac -
counting (Arkema et al. 2017, Barbier 2018). Deter-
mining the metrics of interest and appropriately
interpreting information to inform the management
of ecosystem services presents a complex chal-
lenge that will benefit from interdisciplinary col -
17

Mar Ecol Prog Ser 663: 1–29, 2021
laborations among bioeconomists, social scientists,
and ecologists.
Application. A key premise in landscape ecology is
that ecological function, and hence ecosystem serv-
ices, will vary with the spatial configuration of habi-
tat patches. Integrating seascape ecology concepts
and tools into ecological economics will add realism
to valuations and help to understand the conse-
quences of disruptions to seascape structure and
functional connectivity (Barbier 2018). For example,
the spatial arrangement of habitat patches is now
acknowledged as a factor in the flow, trapping, and
sequestration of organic carbon, but rarely consid-
ered in blue carbon accounting or strategies to
enhance carbon capture (Gullström et al. 2018, Hux-
ham et al. 2018, Fan et al. 2020, Asplund et al. 2021).
Mapping, measuring, and valuing ecosystem serv-
ices across the seascape will provide new bioeco-
nomic, management, and policy insights with impor-
tant implications for targeted management actions
(Spake et al. 2019). With special attention to the 4Cs,
seascape ecology can help identify, characterise, and
assess vulnerabilities and threats to provisioning and
regulatory functions at scales that are relevant to
decision making. In addition, the range of spatial
pattern metrics has broadened to include social land-
scape metrics to map and quantify important areas
for ecosystem service assessments yet have only
been applied on terrestrial landscapes (De Vreese et
al. 2016). A more holistic seascape ecology that
accounts for a broad spectrum of cultural and intrin-
sic values will be important, since narrow socioeco-
nomic values alone can undervalue culturally impor-
tant ocean spaces (Hamel et al. 2018). Modelling and
mapping of the spatial dynamics of marine ecosys-
tem service flows currently lag behind progress in
terrestrial systems, thereby presenting a knowledge-
sharing opportunity on methodological solutions and
18
Fig. 6. Example of seascape connectivity among different patch types in a tropical seascape and the flow of ecosystem serv-
ices. Ecological linkages are depicted by arrows: terrestrial (brown); mangroves (green); seagrasses (blue); and coral reefs
(red). Potential feedbacks from human impacts are also shown (yellow arrows) (adapted from Silvestri & Kershaw 2010)

Pittman et al.: Priority research for seascape ecology
lessons learned. A new holistic seascape framework
that integrates the 4Cs for ecosystem services valua-
tion will require the application and evaluation of a
wide range of tropical and temperate seascapes.
3.6.8. Theme 8: Pelagic seascapes
The highest-priority research question in the
theme of pelagic seascapes was Q20, ranked tenth
by both academic scientists and practitioners. With
23% of votes, this question was placed in the
medium-priority tier. The coastal research bias in
seascape ecology and in marine management in both
respondent groups is likely the reason for very few
questions in this theme.
Q20: What combination of survey and analytical
techniques is most appropriate for characterising
pelagic seascapes?
Research challenges. Concern is growing over
human impacts across the pelagic ocean, particularly
as it remains one of the least understood and most
challenging environments for research and manage-
ment (Dickey-Collas et al. 2017, Ortuño Crespo et al.
2020). Advances in ocean observing systems and
spatial hydrodynamic modelling since the 1970s
have enabled us to map, classify, and track dynamic
spatial structure in the form of eddies, water surface
roughness, currents, runoff plumes, ice cover, temper-
ature fronts, and plankton patches that are detectable
at the ocean surface (Steele 1989, Scales et al. 2014,
Kavanaugh et al. 2016) (Fig. 1). Subsurface structures
such as internal waves, thermo clines, haloclines, or
boundary layers are in creasingly being mapped and
modelled in multiple dimensions (Ryan et al. 2005,
Sayre et al. 2017). These technological advances are
enabling the application of seascape ecology tech-
niques, including novel spatial metrics, to pelagic
waters (Miller 2009, Alvarez-Berastegui et al. 2016)
and the deep seafloor (Bouchet et al. 2015). Signifi-
cant research challenges exist for the application of
seascape ecology to the pelagic ocean, which will
require technological and conceptual innovation and
integration with oceanography (Hidalgo et al. 2016,
Lowerre-Barbieri et al. 2019).
Application. With the integration of satellite data,
ocean sensors, animal telemetry, and geospatial
modelling, studies of pelagic seascapes have demon-
strated that dynamic geometric features (patches,
boundaries, gradients) of the ocean can be geo-
graphically persistent and can help explain ecolog-
ical processes such as animal migrations and for -
aging behaviour (Alvarez-Berastegui et al. 2014,
Scales et al. 2014, Hidalgo et al. 2016, Luo et al.
2020). The inclusion of the vertical dimension of
pelagic seascapes in animal tracking studies is now
generating new insights into mechanistic linkages
between physical processes and marine predator
behaviour, extending conservation prioritisation ver-
tically (Venegas-Li et al. 2018, Braun et al. 2019).
Dynamic ocean management tools that integrate
ecological connectivity already support systematic
conservation planning in the high seas (Dunn et
al. 2016). Hierarchical, multi-dimensional biogeo-
graphic frameworks that incorporate ocean dynamics
are being advanced for pelagic seascapes based on
landscape ecology theory, revealing new insights on
species−seascape relationships (Kavanaugh et al.
2014, Hidalgo et al. 2016, Scales et al. 2018). As
pelagic seascapes change and species shift in re -
sponse to thermal stress, changes in ocean circula-
tion, biological invasions, ocean acidification, and
hypoxia, a major focal area for research will be to test
if, and how, ecological theory and conservation prac-
tices shaped by landscape ecology can be applied to
the open ocean to better inform the design of effec-
tive conservation measures.
3.6.9. Theme 9: Emerging technologies and metrics
The highest-priority research question in the
theme of emerging technologies and metrics was Q6,
ranked fifth by academic scientists and first by prac-
titioners. This places Q6 in the highest-priority tier,
highlighting the importance of reliable quantitative
tools for practitioners and the importance of consid-
ering scale.
Q6: What are the most useful metrics and indica-
tors for characterising and monitoring spatiotemporal
patterns in seascapes, and over what scales should
these be measured?
Research challenges. There is an increasing need
for reliable and meaningful metrics capable of meas-
uring progress towards policy targets and tracking
environmental change (Andries et al. 2019). Policy
indicators will need to be able to measure and visu-
alise the outcome(s) of the policy action(s) efficiently.
Sustainable planning indicators need to be applica-
ble tools that help design and assess plans. A signifi-
cant challenge exists for both science and manage-
ment to develop spatial metrics and indicators that
are both ecologically and operationally relevant,
going beyond simple area metrics for tracking habi-
tat losses or gains. Where habitat is altered, or
removed, the change in spatial pattern and the cas-
19

Mar Ecol Prog Ser 663: 1–29, 2021
cading changes to function are often overlooked.
Spatial pattern metrics (2D and 3D) provide an
opportunity for the development of indicators with
sufficient sensitivity to give early warning of impend-
ing tipping points and ecosystem regime shifts in the
ocean. Discovering which metrics can be used as
indicators for management is an important challenge
that will involve careful evaluation in different envi-
ronments. The pelagic ocean will likely require the
development of new metrics for dynamic fluid sea-
scapes. Sharing of existing time series data (e.g. Bio-
TIME; Dornelas et al. 2018) and new sensors capable
of mapping a wider range of variables at greater spa-
tial and temporal resolution will support a diversifi-
cation of applications for seascape ecology. For
example, innovations such as marine laser altimetry
and multispectral multibeam sonar have significantly
improved the mapping of complex abiotic and biotic
patterns across the seafloor (Collin et al. 2018, Brown
et al. 2019). Additional challenges will include the
development and evaluation of metrics and indica-
tors that capture holistic system properties and
dynamic complexity, including socioecological con-
ditions to inform sustainable development and resili-
ence-based management. Advances in the speed of
acquisition and processing of remotely sensed data
combined with artificial intelligence (geoAI) algo-
rithms (machine learning and deep learning) for
image analyses, data integration, and spatial predic-
tion will likely also lead to new spatial pattern met-
rics and indicators for ocean monitoring and report-
ing (Humphries & Huettmann 2018a, Sun & Scanlon
2019, Sagi et al. 2020). Improved access to marine
data, including crowdsourced geospatial and citizen
science data, and cloud-based platforms for rapid
processing of complex geographical data will improve
the capacity to deliver near-real-time insights for
adaptive marine management (Humphries & Huett -
mann 2018b). The development of 'digital twins' of
the Earth will expand the opportunities for virtual
experiments in seascape ecology to explore complex
scenarios of dynamic pattern-process linkages (Bauer
et al. 2021).
Application. Landscape ecology and other disci-
plines such as geomorphometry and surface metrol-
ogy in industrial engineering have developed a vari-
ety of spatial pattern metrics suitable for measuring
2- and 3-dimensional properties of surface composi-
tion and configuration (Wedding et al. 2011, Bouchet
et al. 2015, Lecours et al. 2016, Frazier & Kedron
2017). Spatial pattern metrics and indicators will help
quantify, characterise, interpret, and communicate
pattern−pattern and pattern−process relationships
and enhance change detection and spatial modelling
(Gustafson 2019, Lacharité & Brown 2019). With a
focus on quantifying spatial patterns at multiple
scales, seascape ecology has expanded the range of
ecologically meaningful patterns and the diversity of
explanatory variables in marine ecology (Wedding et
al. 2011). Spatial pattern metrics vary in their rele-
vance to specific ecological processes, but where a
strong link is evident, changes in metric values can be
indicative of ecological condition and the ability of
seascapes to provide ecosystem services (Santos et
al. 2016, Scales et al. 2018). Seascape ecologists use
suites of metrics/indicators applied to different rep-
resentations of seascape heterogeneity (patch mosaics,
terrains, water volumes) that must be applied with an
understanding of scale effects and associated uncer-
tainty in the link to processes (Wedding et al. 2011).
Novel pattern metrics with special relevance to prac-
titioners may need to be developed and tested through
a transdisciplinary co-production process to ensure
they are operationally relevant for management
(Nassauer & Opdam 2008). Further work is required
into the selection of metrics, their ecological rele-
vance for marine ecosystems, and the evaluation of
scale effects and error propagation, with much to gain
from lessons learned and best practice in applications
to terrestrial landscape planning (Frazier & Kedron
2017, Gustafson 2019). In addition, seascape ecology
has yet to make good use of emerging genetic tech-
niques such as environmental DNA, where spatial
and temporal patterns in species and biodiversity
could be linked to the 4Cs to advance a pattern-
oriented seascape genomics (Grummer et al. 2019).
4. CONCLUSION
We have presented and ranked research priorities
to advance the field of seascape ecology and scanned
the horizon to explore seascape ecology as an emerg-
ing solution-oriented ecological science. The diverse
range of applied research questions and themes listed
here also serves to illustrate the broad interdisciplinary
scope of seascape ecology. By taking landscape ecol-
ogy to the sea, seascape ecology offers an integrative
multi-scale framework with concepts, techniques, and
tools that broaden the range of variables beyond the
conventional ecological toolkit, with potential for new
ecological insights across a range of scales.
To emerge as a transformative science capable of
helping society better protect, restore, and advance
sustainable living, the seascape ecology paradigm
will need to be extended and evolve into a more com-
20

Pittman et al.: Priority research for seascape ecology
prehensive solution-oriented science, as have sectors
of landscape ecology (Wu 2006, 2013, Opdam et al.
2018). Seascape ecologists will need to span aca-
demic and practitioner boundaries, understand the
operational opportunities and constraints of marine
management practice, share knowledge, make code
and data more easily available, and seek out oppor-
tunities for transdisciplinary research (Keeler et al.
2017, Saord et al. 2017). By ‘transdisciplinary’, we
mean research that has both interactions across disci-
plines and participation from relevant non-academic
sectors of society. Further collaborative research pri-
oritisation efforts with greater dialogue between aca-
demic scientists and management practitioners are
required to co-formulate research questions and co-
develop projects that demonstrate the application of
seascape ecology (Cvitanovic et al. 2016, Dey et al.
2020, Fisher et al. 2020).
Development of a holistic seascape ecology frame-
work that considers the full range of factors connect-
ing people and the sea within a coupled socio -
ecological system is required (Pittman et al. 2018).
The development of a more holistic transdisciplinary
and multiple scale approach in seascape ecology is
consistent with addressing the sustainable develop-
ment goals (SDGs) identified by the UN 2030 Agenda
for Sustainable Development. The reach of seascape
ecology extends beyond SDG14 'Life Below Water'
(Rees et al. 2018b) and recognises the interlinkages
among SDGs, particularly those re lated to food secu-
rity, energy, sustainable living, and climate change
(i.e. multi-SDG nexus), where a spatially explicit and
integrative multi-scale systems approach can form a
useful framework for a sustainability science (Liu et
al. 2015). The conceptual and operational shift to a
seascape ecology approach has generated a wide
range of new and fundamental questions in ecology,
where explicit consideration of the 4Cs (context, con-
figuration, connectivity, and consideration of scale) is
of critical importance to efforts to restore and support
a thriving ocean.
Acknowledgements. We are grateful to the many practi-
tioner respondents for the time taken to engage with our
questionnaire. K.L.Y. was funded by a NERC Knowledge
Exchange Fellowship NE/P00668X/1. We thank R. M. Starr
and 2 anonymous reviewers, who provided comments that
helped improve the manuscript.
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28
Appendix. Full list of author addresses
S. J. Pittman1,2,*, K. L. Yates3, P. J. Bouchet4,5, D. Alvarez-Berastegui6, S. Andréfouët7,
S. S. Bell8, C. Berkström9,10, C. Boström11, C. J. Brown12, R. M. Connolly13,
R. Devillers14, D. Eggleston15, B. L. Gilby16, M. Gullström17, B. S. Halpern18,19,
M. Hidalgo20, D. Holstein21, K. Hovel22, F. Huettmann23, E. L. Jackson24, W. R. James25,
J. B. Kellner26, C. Y. Kot27, V. Lecours28, C. Lepczyk29, I. Nagelkerken30,
J. Nelson21, A. D. Olds16, R. O. Santos31, K. L. Scales16, D. C. Schneider32,
H. T. Schilling33, 34, C. Simenstad35, I. M. Suthers33, 34, E. A. Treml36, L. M. Wedding1, P.
Yates34,37, M. Young36
1Oxford Seascape Ecology Lab, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK
2Project Seascape CIC, Plymouth, PL2 1RP, UK
3School of Science, Engineering & Environment, University of Salford, Manchester, M5 4WT, UK
4School of Mathematics & Statistics, University of St. Andrews, St. Andrews, Fife, KY16 9SS, UK
5Centre for Research into Ecological & Environmental Modelling, University of St. Andrews, St. Andrews, Fife,
KY16 9LZ, UK
6Balearic Islands Coastal Observing and Forecasting System, 07121 Palma de Mallorca, Mallorca, Spain
7Institut de Recherche pour le Développement, UMR 9220 ENTROPIE, (Université de la Réunion, IFREMER,
Université de la Nouvelle-Calédonie, Centre National de la Recherche Scientifique), Nouméa, New-Caledonia
8Department of Integrative Biology, University of South Florida, Florida, FL 33620, USA

Pittman et al.: Priority research for seascape ecology 29
Editorial responsibility: Myron Peck,
Den Burg, The Netherlands
Reviewed by: R. M. Starr and 2 anonymous referees
Submitted: September 12, 2020
Accepted: February 9, 2021
Proofs received from author(s): March 23, 2021
9Department of Aquatic Resources, Institute of Coastal Research, Swedish University of Agricultural Sciences,
Skolgatan 6, 742 42 Öregrund, Sweden
10Department of Ecology, Environment and Plant Sciences (DEEP), Stockholm University, SE 106 91, Stockholm, Sweden
11Environmental and Marine Biology, Åbo Akademi University, Artillerigatan 6, 20520, Åbo, Finland
12Department of Oceanography, Dalhousie University, Halifax, Nova Scotia, B3H 4R2, Canada
13Australian Rivers Institute – Coast & Estuaries, School of Environment and Science, Griffith University,
Queensland, QLD 4222, Australia
14Institut de Recherche pour le Développement, UMR 228 ESPACE-DEV (Univ. Montpellier, IRD, Univ. Antilles,
Univ. Guyane, Univ. Réunion), 34393 Montpellier, France
15Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh,
North Carolina, NC 27695, USA
16School of Science and Engineering, University of the Sunshine Coast, Maroochydore, Queensland 4558, Australia
17School of Natural Sciences, Technology and Environmental Studies, Södertörn University, 141 89 Huddinge,
Stockholm, Sweden
18National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, California, CA 93101, USA
19Bren School of Environmental Science and Management, University of California, Santa Barbara, California,
CA 93106, USA
20Instituto Español de Oceanografía, Centre Oceanográfic de les Balears, Ecosystem Oceanography Group (GRECO),
07015 Palma de Mallorca, Mallorca, Spain
21Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, Louisiana, LA 70803, USA
22Department of Biology, Coastal & Marine Institute, San Diego State University, San Diego, California, CA 92101, USA
23EWHALE Lab, Institute of Arctic Biology, Biology & Wildlife Department, University of Alaska Fairbanks,
Fairbanks, Alaska, AK 99775, USA
24Coastal Marine Ecosystems Research Centre, Central Queensland University, Gladstone, Queensland, QLD 4680, Australia
25Department of Biology, University of Louisiana, Lafayette, Louisiana, LA 70504, USA
26International Council for the Exploration of the Sea (ICES), 1553 Copenhagen V, Denmark
27Marine Geospatial Ecology Lab, Nicholas School of the Environment, Duke University, Beaufort, North Carolina,
NC 28516, USA
28Geomatics Program and Fisheries & Aquatic Sciences Program, School of Forest Resources & Conservation,
University of Florida, Florida, FL 32611, USA
29School of Forestry and Wildlife Sciences, Auburn University, Auburn, Alabama, AL 36849, USA
30Southern Seas Ecology Laboratories, School of Biological Sciences and the Environment Institute, The University
of Adelaide, South Australia, SA 5005, Australia
31Institute of Environment, Florida International University, Miami, Florida, FL33199, USA
32Department of Ocean Sciences, Memorial University of Newfoundland, Newfoundland, A1B 3X7, Canada
33School of Biological, Earth, and Environmental Sciences, University of New South Wales, Sydney, New South Wales,
NSW 2052, Australia
34Sydney Institute of Marine Science, Mosman, New South Wales, NSW 2088, Australia
35School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, WA 98195-5020, USA
36School of Life and Environmental Sciences, Centre for Integrative Ecology, Deakin University, Victoria,
VIC 3216, Australia
37Present address: Marine and Freshwater Species Conservation, Biodiversity Conservation Division, Department of
Agriculture, Water and the Environment, Canberra ACT 2601, Australia