# Seascape ecology: identifying research priorities for an emerging ocean sustainability science

S. J. Pittman, K. L. Yates, P. J. Bouchet, D. Alvarez-Berastegui, S. Andréfouët, S. S. Bell, C. Berkström, C. Boström, C. J. Brown, R. M. Connolly, et al.

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► To cite this version:

S. J. Pittman, K. L. Yates, P. J. Bouchet, D. Alvarez-Berastegui, S. Andréfouët, et al., Seascape ecology: identifying research priorities for an emerging ocean sustainability science. Marine Ecology Progress Series, 2021, 663, pp.1-29. 10.3354/meps13661. http://hal-03277734

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# Seascape ecology: identifying research priorities for an emerging ocean sustainability science

S. J. Pittman<fnref n="1" />,<fnref n="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. Wedding<fnref n="1" />, P. Yates³⁴,³⁷, M. Young³⁶

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 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 2-stage modified Delphi method to solicit applied research questions 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).

<figure><img src="image_4.png" /></figure>

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

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 intriguing

© 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.

<footnote n="1">¹Oxford Seascape Ecology Lab, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK</footnote>

<footnote n="2">²Project Seascape CIC, Plymouth PL2 1RP, UK</footnote>

<footnote>*Corresponding author: sjpittman@gmail.com</footnote>
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 collecting, mapping, and sharing of ocean data, the gap between 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, fundamental 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 biodiversity 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 connectivity, 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 addressed through the integrative, multi-scale and pattern-oriented conceptual framework of landscape ecology (Turner 1989, Ray 1991, Wedding et al. 2011, Pittman 2018b). Landscape ecologists seek to understand the causes and consequences of spatial complexity (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 represent 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, fragmentation) 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 containing 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 systems properties present diagnostic attributes for understanding structure-function relationships and evaluating system status that are key to implementation 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, configuration, connectivity, and the consideration of scale, an all-pervading concept. The term 'configuration' 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 landscape 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 ecological 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 (Simberloff & 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 single large patch or several small patches (e.g. sea-grasses: McNeill & Fairweather 1993; patch reefs: Schroeder 1987). At the time when landscape ecol-
<figure><img src="image_5.png" /><figcaption>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)</figcaption></figure>

ogy emerged as an ecological science, observations of fish movements were beginning to shed light on the influence of seascape configuration on functional 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 environment. Research has primarily focussed on benthic seascapes, sometimes referred to as benthoskapes (Zajac et al. 2000, Brown et al. 2011, Proudfoot 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 & Furman 2017). Renewed focus on 'ocean landscapes' (sensu Steele 1989), now referred to as pelagic seascapes (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 gradually 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 volumes 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 development of seascape ecology as a sustainability science for the ocean. The effective application of an integrative multi-scale conceptual and operational framework is required for the interpretation of complex
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 ecology. 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 development 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/m663p001_supp.pdf):

(1) Questions must be of broad geographical relevance, but can be focussed on any scale, with the condition that the question relates to measurable spatial patterns, patterning processes, or pattern-process relationships.

<figure><img src="image_6.png" /><figcaption>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</figcaption></figure>
(2) Questions must address a knowledge gap that will advance the practice of marine management, conservation, and marine spatial planning if adequately addressed within a decade.

### 2.1.1. Selection of participants

*Academic scientists.* We identified and invited 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 invitees to suggest suitable colleagues (i.e. referral sampling). Specialised ecological knowledge among the academics included fish and fisheries, seabirds, biological oceanography, ecoinformatics, remote sensing and habitat mapping, coral reef ecosystems, and saltmarsh and seagrass ecology, with research being conducted across a wide range of focal scales and geographical locations in temperate and tropical ecoregions.

*Practitioners.* We identified and invited 105 practitioners who were primarily senior staff at inter-governmental, governmental (national and local), or non-governmental organisations, and specialist marine 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 addressed by the academics' research questions, coordinators 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 results. 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 remained anonymous to all participants other than the coordinators. Respondents were asked to self-assess their familiarity with seascape ecology on a discrete scale ranging from 1 (no knowledge) to 5 (expert), in half-point increments. 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 important 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 questions into 3 priority classes using upper, middle, and lower terciles, whereby highest priorities are questions 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 coordinators' intention to classify the responses into 3 priority classes and had no knowledge of the intention to compare academic scientist priorities with practitioner priorities. Zeros were noted where a question was not selected. Cross-comparison of priority classes was conducted using a confusion matrix to evaluate the agreement between academics and practitioners. An unpaired 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 accepted the invitation to participate and submitted applied research questions and then fully completed the prioritisation questionnaire. Academics were affiliated with research institutions located in 9 countries
(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 seascape ecology (Fig. 3). Six practitioners had low familiarity (score 1–2) with seascape ecology. The academic 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 included in the analyses. The lower familiarity with seascape ecology among practitioner respondents presents a key challenge to the transmission of results from seascape ecology into practice. Improving awareness of seascape ecology, however, can be addressed through co-design of demonstration projects, 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 governance, 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 significant loss of key information from the original submissions, 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 technologies and metrics (Table 1). Some questions were relevant to multiple themes but were placed in a single theme for analysis. The largest grouping of questions occurred under the following 3 themes: (1) seascape 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 'restoration and sustainability science', where 18 questions exhibiting considerable overlap were consolidated into 4 distinct questions. No additional research questions were received from practitioners.

## 3.3. Relative importance among the 55 research questions

From the 55 research questions presented to respondents in the questionnaire (Step 2, Fig. 2), the academic 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 planning. The research themes 'spatial and temporal scale' and 'emerging technologies and metrics' were considered 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

<figure><img src="image_7.png" /><figcaption>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</figcaption></figure>
<table><caption>Table 1. Results of the curation process to reduce redundancy in content across all research questions grouped within 9 research themes</caption><thead><tr><th>Research theme</th><th>Number of questions submitted</th><th>Number of questions post-curation</th></tr></thead><tbody><tr><td>1. Seascape change<br>Dynamic spatial patterns and the ecological and social consequences of structural change</td><td>29</td><td>11</td></tr><tr><td>2. Seascape connectivity<br>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</td><td>24</td><td>10</td></tr><tr><td>3. Restoration and sustainability science<br>Holistic spatial frameworks and systems science to inform human actions to address the challenges of sustainability</td><td>18</td><td>4</td></tr><tr><td>4. Ecosystem-based management<br>Ecological systems approach to management including spatial management strategies</td><td>16</td><td>10</td></tr><tr><td>5. Seascape mapping, modelling, sampling<br>Spatially explicit pattern-oriented and multi-scale analytical methods and tools</td><td>11</td><td>8</td></tr><tr><td>6. Spatial and temporal scale<br>Scale selection, scale effects, and multi-scale frameworks</td><td>10</td><td>3</td></tr><tr><td>7. Seascape goods and services<br>Spatial patterns and ecological processes underpinning ecosystem services with a focus on spatial context, configuration, and connectivity</td><td>9</td><td>3</td></tr><tr><td>8. Pelagic seascapes<br>Dynamic spatial patterns and ecological processes in the open ocean and the linkages to benthic ecology</td><td>7</td><td>2</td></tr><tr><td>9. Emerging technologies and metrics<br>Spatial ecoinformatics, geospatial technologies, and advanced computing including artificial intelligence</td><td>4</td><td>4</td></tr><tr><td>Total</td><td>128</td><td>55</td></tr></tbody></table>

<figure><img src="image_8.png" /><figcaption>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</figcaption></figure>
<table><caption>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)</caption><thead><tr><th>Priority tier</th><th>Research themes and questions</th></tr></thead><tbody><tr><td>Academics Practitioners</td><td></td></tr><tr><td><strong>1. Seascape change</strong></td><td></td></tr><tr><td>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?</td><td>1</td><td>2</td></tr><tr><td>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?</td><td>1</td><td>2</td></tr><tr><td>Q22. How do range extensions or contractions of habitat-forming species alter seascapes and their function?</td><td>2</td><td>3</td></tr><tr><td>Q13. How can seascape ecology help set ecologically meaningful goals and targets for management in a changing ocean?</td><td>1</td><td>1</td></tr><tr><td>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?</td><td>3</td><td>1</td></tr><tr><td>Q36. How can seascape ecology inform ecological risk assessments of anthropogenic impacts (e.g. climate change)?</td><td>3</td><td>2</td></tr><tr><td>Q46. How will climate change and other anthropogenic impacts that influence landscape conditions impact coastal seascapes?</td><td>3</td><td>2</td></tr><tr><td><strong>2. Seascape connectivity</strong></td><td></td></tr><tr><td>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)?</td><td>1</td><td>1</td></tr><tr><td>Q12. How does connectivity modify the resistance to disturbance and recovery of ecological entities (from populations to ecosystems)?</td><td>1</td><td>3</td></tr><tr><td>Q14. How do different seascapes contribute to patterns of dispersal for species expanding their range (e.g. invasive, re-locations, climate shifting, recovering populations)?</td><td>1</td><td>3</td></tr><tr><td>Q15. How can seascape ecology be used to prioritise efforts to manage (enhance; maintain; mitigate) connectivity?</td><td>2</td><td>1</td></tr><tr><td>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?</td><td>2</td><td>2</td></tr><tr><td><strong>3. Restoration and sustainability science</strong></td><td></td></tr><tr><td>Q5. How can seascape ecology inform the design and assessment of seascape restoration and creation efforts to improve success?</td><td>1</td><td>1</td></tr><tr><td>Q29. How can we best integrate a holistic systems approach into seascape ecology to serve as a sustainability science for the ocean?</td><td>2</td><td>1</td></tr><tr><td><strong>4. Ecosystem-based management</strong></td><td></td></tr><tr><td>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)?</td><td>1</td><td>1</td></tr><tr><td>Q16. How can seascape connectivity be integrated into marine spatial planning?</td><td>2</td><td>2</td></tr><tr><td>Q18. How can seascape ecology contribute to fisheries management by considering spatial variability in pelagic seascapes?</td><td>2</td><td>3</td></tr><tr><td>Q23. What attributes of seascape patterns can be used to provide metrics or indicators to determine ecosystem health?</td><td>2</td><td>1</td></tr><tr><td>Q28. How can seascape ecology be applied to support the monitoring and assessment of management actions to evaluate their effectiveness?</td><td>2</td><td>1</td></tr><tr><td>Q31. How can seascape ecology enhance ecosystem-based management in the open oceans?</td><td>2</td><td>2</td></tr><tr><td>Q38. How do the effects of seascape context and connectivity modify conservation outcomes, and over what scales for which species and ecosystems?</td><td>3</td><td>2</td></tr><tr><td>Q41. What are the needs of coastal managers to increase their capacity to use a seascape approach?</td><td>3</td><td>2</td></tr><tr><td><strong>5. Seascape mapping, modelling, and sampling design</strong></td><td></td></tr><tr><td>Q10. How can seascape ecology be used to improve ecological modelling for predicting the geographical distribution of bioa?</td><td>1</td><td>2</td></tr><tr><td>Q48. How much structural detail do we need to include when making habitat maps to detect and explain ecologically meaningful spatial patterns?</td><td>3</td><td>1</td></tr><tr><td><strong>6. Spatial and temporal scale</strong></td><td></td></tr><tr><td>Q19. What are the appropriate spatial and temporal scales for assessments of seascape resilience?</td><td>2</td><td>2</td></tr><tr><td>Q2. How should seascape ecology identify the relevant spatial and temporal scales over which patterns and processes are linked to inform management practices?</td><td>1</td><td>1</td></tr><tr><td>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?</td><td>1</td><td>2</td></tr><tr><td><strong>7. Seascape goods and services</strong></td><td></td></tr><tr><td>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?</td><td>1</td><td>1</td></tr><tr><td>Q21. How do seascAPE patterns influence the flow and quality of ecosystem goods and the estimation of value and risk in natural capital assessments?</td><td>2</td><td>2</td></tr><tr><td>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?</td><td>3</td><td>1</td></tr><tr><td><strong>8. Pelagic seascapes</strong></td><td></td></tr><tr><td>Q20. What combination of survey and analytical techniques are most appropriate for characterising pelagic seascapes?</td><td>2</td><td>2</td></tr><tr><td><strong>9. Emerging technologies and metrics</strong></td><td></td></tr><tr><td>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?</td><td>1</td><td>1</td></tr><tr><td>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)?</td><td>1</td><td>2</td></tr><tr><td>Q24. How can we use emerging sensor technologies and data integration techniques to improve seascape mapping?</td><td>2</td><td>1</td></tr></tbody></table>
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%) priorities (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 questions selected in Step 3 by more than 40% of academic 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 priority in Step 3 (39 and 32%) (Table S2). Q3 was important to 65% of practitioners in Step 2 and ranked tenth of 55 questions in Step 3. Combining the proportion 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 difference in the proportion of votes received by each respondent 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 disagreement 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 practitioners, and 3 of the lowest-priority questions for academic 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 questions 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 priorities 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 (Cvitanovic et al. 2013). For instance, the highest-ranking

(52% of the vote) question (Q6) in the practitioners' top 10 was ranked fifth by academic scientists and focussed on identifying and applying useful metrics and indicators to characterise and monitor spatio-temporal seascape patterns. The greatest between-group difference, 28% higher for practitioners than academic scientists, was for Q28 on support for monitoring and assessment of the effectiveness of management actions. Question 22 on the impact of species range extensions 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 diverging priorities represent an important difference in priority setting. This misalignment reflects the greater emphasis for practitioners on the need for science to support advances in monitoring and assessment, including 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 priority than research questions that focussed on marine organisms. For instance, Q35 on understanding human 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 metapopulations and teleconnections received zero selections

<table><caption>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 proportion of agreement between respondent groups for each priority class</caption><thead><tr><th rowspan="2">Priority</th><th colspan="3">Academic scientists</th><th rowspan="2">Total</th></tr><tr><th>Highest</th><th>Medium</th><th>Lowest</th></tr></thead><tbody><tr><td>Practitioners</td><td></td><td></td><td></td><td></td></tr><tr><td>Highest</td><td>7<br>(50%)</td><td>5<br>(26%)</td><td>3<br>(14%)</td><td>15</td></tr><tr><td>Medium</td><td>5<br>(36%)</td><td>6<br>(32%)</td><td>6<br>(27%)</td><td>17</td></tr><tr><td>Lowest</td><td>2<br>(14%)</td><td>8<br>(42%)</td><td>13<br>(59%)</td><td>23</td></tr><tr><td>Total</td><td>14</td><td>19</td><td>22</td><td>55</td></tr></tbody></table>
<figure><img src="image_9.png" /><figcaption>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 tertile questions (blue) represent the highest priority, and lower tertile questions (light blue) represent the lowest priority</figcaption></figure>

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), research 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. Although 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. Although 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
provided in Table 2 (and Tables S1 & S2). To context-
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 conditions, and primary productivity) on seascape structure and function?

Q13: How can seascape ecology help set ecologically 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 advances in data integration and a sea-
scape ecology framework capable of adopting sys-
tems science concepts and techniques and the
capacity to integrate information 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.
### 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 management actions, and what connections are most critical for ecosystem function, biodiversity, and ecosystem services (provisioning, regulating, supporting)?

Q15: How can seascape ecology be used to prioritise efforts to manage (enhance, maintain, mitigate) connectivity?

**Research challenges.** In many locations, it remains unclear how human activities have modified the material flux between landscapes and seascapes 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 functions enhance ecosystem services and conservation outcomes (Olds et al. 2016, Weeks 2017, Theuerkauf et al. 2019). This also extends to often complex interactions between distant places (telecoupling) that can lead to unexpected outcomes with important 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 revealed mass fish migrations synchronised with seasonal cycles of primary productivity, 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 socioeconomic 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 provisioning 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 seascape ecology. Seascape connectivity describes the degree to which a seascape facilitates or hinders the movement of organisms, or the flow of genetic material, nutrients, and other matter (Grober-Dunsmore et al. 2009). Seascape ecology can help advance the integration of seascape connectivity into decision support tools and best practice principles that inform actions that maintain connectivity and rehabilitate dysfunctional connectivity (Watson et al. 2017, Waltham et al. 2019). Furthermore, better integration of seascape structure and function into coupled biophysical connectivity modelling will improve tools to predict pathways and consequences of invasive species, pathogens (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 modelling actual, structural, and potential connectivity have been created and applied to terrestrial landscapes, 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 distributions (Lowe & Allendorf 2010, Treml et al. 2015, Puckett & Eggleston 2016). Graph-theoretical methods, as used in landscape ecology, provide an effective 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, Saunders et al. 2016). Neutral seascape models allow us to test and explore through spatial simulations the influence of simplified seascape configuration, hydrodynamics, and scale on organism space-use strategies (Caldwell & Gergel 2013). Dynamic models of potential connectivity, especially propagule dispersal, 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 seascapes and between land and sea. For example, the fisheries ecosystem service value can be influenced by seascape connectivity of coastal marine ecosystems, with well-documented examples including interconnected nursery habitats referred to as 'seascape nurseries' (Nagelkerken et al. 2015, Perry et al.
2018, Berkström et al. 2020). Identification of areas of critical habitat and ecological connectivity for sustaining biodiversity and ecosystem services is increasingly required for spatial conservation planning (Mumby 2006, Weeks 2017, Yates et al. 2019, Proudfoot et al. 2020).

Spatial pattern metrics quantifying benthic seascape connectivity can help design protected areas that maximise structural connectivity (Engelhard et al. 2017, Weeks 2017, Proudfoot et al. 2020). Improved functionality in spatial planning software enables data on actual and potential ecological connectivity 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 capability to understand and better manage vertical connectivity (e.g. nutrient exchange) coupling benthic and pelagic components (Griffiths et al. 2017). Seascape ecology must also begin to include the multi-scale spatial patterns and processes of the often overlooked 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 microscopic 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 scientists 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 support the monitoring and assessment of management actions to evaluate their effectiveness?

**Research challenges.** Calls for more holistic and inclusive approaches to marine management and conservation that consider local ecological knowledge and social justice (Bennett 2018) present important challenges for scientific research and for the evolution of a sustainability science for the ocean. EBM is an integrated 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 design of MPAs, coherent MPA networks, and broader marine spatial planning (Roberts et al. 2003, Crowder & Norse 2008, Foley et al. 2010). For example, achieving qualitative elements of the Aichi Biodiversity Target 11 by 2020 required spatially explicit information on the 4Cs of seascape ecology to design 'ecologically representative and well-connected systems of protected 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 practice (Rees et al. 2018a,b, Meehan et al. 2020).

**Application.** With a focus on multi-scale system complexity, we suggest that seascape ecology provides an appropriate framework to enhance the contribution of ecological science to both goal setting and provisioning of evidence when addressing biodiversity conservation and sustainable development goals. Concepts familiar to landscape and seascape ecologists such as ecological connectivity, corridors, ecological networks, scale-effects, and habitat fragmentation permeate marine conservation and spatial planning through EBM (Crowder & Norse 2008). Similarly, core concepts from landscape ecology increasingly bridge the science-policy gap, playing a central role in national and global policy for biodiversity conservation, restoration, and sustainable development (Choi et al. 2008, Opdam et al. 2018, Rees et al. 2018a, Balbar & Metaxas 2019).

From an operational perspective, adaptive monitoring will require spatial pattern metrics that reflect function, including novel ocean-specific metrics capable of serving as condition indicators (e.g. frontal densities, 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 conservation action have been ecologically refined with principles 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 framework (Matta & Serra 2016), could facilitate the integration of seascape patterns into holistic ecosystem assessments (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
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 ecological 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 managing 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 'sustainable blue economy' will rise in prominence with the rapid growth and diversification of ocean and coastal uses (Huettmann & Czech 2006, Jouffray 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 scientists, management practitioners, industry, and community groups.

In 2019, the UN General Assembly declared 2021–2030 the ‘UN Decade on Ecosystem Restoration’, calling for accelerated global action to restore degraded ecosystems (Duarte et al. 2020). Restoration of coastal seascapes, however, presents a complex 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 projects revealed that only 13% considered landscape

context in site selection, yet of those that did, 60% supported larger and more diverse animal populations than control areas (Gilby et al. 2018b). Spatially explicit and ecology informed transdisciplinary approaches stand to benefit habitat and seascape restoration through optimal site selection, enhanced ecological design, improved prediction of post-restoration 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 consequences for neighbouring areas will advance seascape 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 attributes 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 spatial 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 seascape type, promotes a more comprehensive consideration of species connectivity, seascape configuration, community-level processes, external threats, feedback loops, ecosystem service flows, and connectivity 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 potential to provide spatial design principles for seascape restoration based on the 4Cs.

Active restoration projects present excellent opportu-
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
design scenarios, and analyse trade-offs to guide actions (Sleeman et al. 2005, Brudvig et al. 2017, Lester et al. 2020). Although rarely examined, knowledge of seascape configuration could provide information 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 knowledge 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 academic scientists, highlighting a substantial (23%) divergence of agreement between the 2 groups.

Q10: How can seascape ecology be used to improve ecological modelling for predicting the geographical 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 pervasive challenge in marine ecology and management (Levin 1992, Capotondi et al. 2019). A significant outstanding challenge lies in developing mapping techniques that incorporate dynamic processes, including sub-surface patterns (Brodie et al. 2018), to facilitate the linking of structure and function. Geospatial products such as benthic habitat maps and maps of pelagic structure (e.g. ocean fronts) are important spatial data that enable ecological analyses 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 methodological challenges associated with thematic and spatial resolution, as well as temporal dynamics (Lechner & Rhodes 2016). Mismatches between ecological, observational, and analytical scales can

be problematic because they can bias species-habitat relationships and constrain ecological questions (Brown et al. 2011, Lecours et al. 2015). Increasingly, however, targeted research-led mapping has focussed on capturing ecological patterns that specifically consider species, communities, and biodiversity 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 seascapes 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 management in fisheries and meet conservation objectives 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 important role to play in sampling design, particularly when assessing human impacts and monitoring the effectiveness of management actions (Hewitt et al. 2007, Sandel & Smith 2009). The potential for bias from inadequate consideration of variability in the 4Cs has received little attention in both landscape and seascape ecology, yet has considerable implications for data acquisition, analyses, and interpretation.

**Application.** Seascape mapping enables the acquisition 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 primary use of seascape maps has been to quantify and compare seascape patterns and pattern-forming processes 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 resources 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-
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 (Huettmann & 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 practitioners. 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 academic 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 inappropriate scale selection can result in inflated uncertainty, 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 consequences for the interpretation of results, with different patterns emerging at different scales of investigation (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 uncertainty in EBM (Glaser & Glaeser 2014). The appropriate 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 identification of causative variables and impede the application of science to practice (Wolkovich et al. 2014).
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 seascape ecology and has resulted in significant advancement in our conceptualisation and methodological consideration of scale and scaling (Wiens 1989). Unsurprisingly, many of the research questions formulated by academic scientists, such as presented 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 hierarchies 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 benefits in terms of biodiversity and productivity, support optimal functional connectivity, and how will these functions change through re-structuring processes 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-
<figure><img src="image_10.png" /><figcaption>Fig. 6. Example of seascape connectivity among different patch types in a tropical seascape and the flow of ecosystem services. 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)</figcaption></figure>

laborations among bioeconomists, social scientists, and ecologists.

*Application.* A key premise in landscape ecology is that ecological function, and hence ecosystem services, will vary with the spatial configuration of habitat patches. Integrating seascape ecology concepts and tools into ecological economics will add realism to valuations and help to understand the consequences 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 considered in blue carbon accounting or strategies to enhance carbon capture (Gullström et al. 2018, Huxham et al. 2018, Fan et al. 2020, Asplund et al. 2021). Mapping, measuring, and valuing ecosystem services across the seascape will provide new bioeconomic, 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 landscape 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 intrinsic values will be important, since narrow socioeconomic values alone can undervalue culturally important ocean spaces (Hamel et al. 2018). Modelling and mapping of the spatial dynamics of marine ecosystem service flows currently lag behind progress in terrestrial systems, thereby presenting a knowledge-sharing opportunity on methodological solutions and
lessons learned. A new holistic seascape framework that integrates the 4Cs for ecosystem services valuation 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 management (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, temperature 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, thermoclines, haloclines, or boundary layers are increasingly 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 techniques, including novel spatial metrics, to pelagic waters (Miller 2009, Alvarez-Berastegui et al. 2016) and the deep seafloor (Bouchet et al. 2015). Significant 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 demonstrated that dynamic geometric features (patches, boundaries, gradients) of the ocean can be geographically persistent and can help explain ecological processes such as animal migrations and foraging 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 vertically (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 biogeographic 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 response to thermal stress, changes in ocean circulation, biological invasions, ocean acidification, and hypoxia, a major focal area for research will be to test if, and how, ecological theory and conservation practices shaped by landscape ecology can be applied to the open ocean to better inform the design of effective 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 practitioners. This places Q6 in the highest-priority tier, highlighting the importance of reliable quantitative tools for practitioners and the importance of considering scale.

Q6: What are the most useful metrics and indicators 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 measuring progress towards policy targets and tracking environmental change (Andries et al. 2019). Policy indicators will need to be able to measure and visualise the outcome(s) of the policy action(s) efficiently. Sustainable planning indicators need to be applicable tools that help design and assess plans. A significant challenge exists for both science and management to develop spatial metrics and indicators that are both ecologically and operationally relevant, going beyond simple area metrics for tracking habitat losses or gains. Where habitat is altered, or removed, the change in spatial pattern and the cas-
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 impending 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 environments. The pelagic ocean will likely require the development of new metrics for dynamic fluid seascapes. 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 spatial and temporal resolution will support a diversification 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 indicators that capture holistic system properties and dynamic complexity, including socioecological conditions to inform sustainable development and resilience-based management. Advances in the speed of acquisition and processing of remotely sensed data combined with artificial intelligence (geoAI) algorithms (machine learning and deep learning) for image analyses, data integration, and spatial prediction will likely also lead to new spatial pattern metrics and indicators for ocean monitoring and reporting (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 & Huettmann 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 disciplines such as geomorphometry and surface meteorology in industrial engineering have developed a variety of spatial pattern metrics suitable for measuring 2- and 3-dimensional properties of surface composition 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 relevance 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 representations of seascape heterogeneity (patch mosaics, terrains, water volumes) that must be applied with an understanding of scale effects and associated uncertainty in the link to processes (Wedding et al. 2011). Novel pattern metrics with special relevance to practitioners 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 relevance 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 techniques 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 emerging 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 ecology 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-
preprehensive solution-oriented science, as have sectors of landscape ecology (Wu 2006, 2013, Opdam et al. 2018). Seascape ecologists will need to span academic 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 opportunities for transdisciplinary research (Keeler et al. 2017, Safford et al. 2017). By 'transdisciplinary', we mean research that has both interactions across disciplines and participation from relevant non-academic sectors of society. Further collaborative research prioritisation efforts with greater dialogue between academic 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 framework that considers the full range of factors connecting 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 development 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 related to food security, 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, configuration, 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 practitioner 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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Appendix. Full list of author addresses

S. J. Pittman<sup>1,2,*</sup>, K. L. Yates<sup>3</sup>, P. J. Bouchet<sup>4,5</sup>, D. Alvarez-Berastegui<sup>6</sup>, S. Andréfouët<sup>7</sup>, S. S. Bell<sup>8</sup>, C. Berkström<sup>9,10</sup>, C. Boström<sup>11</sup>, C. J. Brown<sup>12</sup>, R. M. Connolly<sup>13</sup>, R. Devillers<sup>14</sup>, D. Eggleston<sup>15</sup>, B. L. Gilby<sup>16</sup>, M. Gullström<sup>17</sup>, B. S. Halpern<sup>18,19</sup>, M. Hidalgo<sup>20</sup>, D. Holstein<sup>21</sup>, K. Hovel<sup>22</sup>, F. Huettmann<sup>23</sup>, E. L. Jackson<sup>24</sup>, W. R. James<sup>25</sup>, J. B. Kellner<sup>26</sup>, C. Y. Kot<sup>27</sup>, V. Lecours<sup>28</sup>, C. Lepczyk<sup>29</sup>, I. Nagelkerken<sup>30</sup>, J. Nelson<sup>21</sup>, A. D. Olds<sup>16</sup>, R. O. Santos<sup>31</sup>, K. L. Scales<sup>16</sup>, D. C. Schneider<sup>32</sup>, H. T. Schilling<sup>33,34</sup>, C. Simenstad<sup>35</sup>, I. M. Suthers<sup>33,34</sup>, E. A. Treml<sup>36</sup>, L. M. Wedding<sup>1</sup>, P. Yates<sup>34,37</sup>, M. Young<sup>36</sup>

<footnote n="1"><sup>1</sup>Oxford Seascape Ecology Lab, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK</footnote>

<footnote n="2"><sup>2</sup>Project Seascape CIC, Plymouth, PL2 1RP, UK</footnote>

<footnote n="3"><sup>3</sup>School of Science, Engineering & Environment, University of Salford, Manchester, M5 4WT, UK</footnote>

<footnote n="4"><sup>4</sup>School of Mathematics & Statistics, University of St. Andrews, St. Andrews, Fife, KY16 9SS, UK</footnote>

<footnote n="5"><sup>5</sup>Centre for Research into Ecological & Environmental Modelling, University of St. Andrews, St. Andrews, Fife, KY16 9LZ, UK</footnote>

<footnote n="6"><sup>6</sup>Balearic Islands Coastal Observing and Forecasting System, 07121 Palma de Mallorca, Mallorca, Spain</footnote>

<footnote n="7"><sup>7</sup>Institut 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</footnote>

<footnote n="8"><sup>8</sup>Department of Integrative Biology, University of South Florida, Florida FL 33620, USA</footnote>
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 Oceanogràfic 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