Ecology

COMMENT
26 July 2021

Biodiversity needs every tool in the box: use OECMs

To conserve global biodiversity, countries must forge equitable alliances that support sustainability in traditional pastoral lands, fisheries-management areas, Indigenous territories and more.

Georgina G. Gurney

0
,

Emily S. Darling

1
,

Gabby N. Ahmadia

2
,

Vera N. Agostini

3
,

Natalie C. Ban

4
,

Jessica Blythe

5
,

Joachim Claudet

6
,

Graham Epstein

7
,

Estradivari

8
,

Amber Himes-Cornell

9
,

Harry D. Jonas

10
,

Derek Armitage

11
,

Stuart J. Campbell

12
,

Courtney Cox

13
,

Whitney. R. Friedman

14
,

David Gill

15
,

Peni Lestari

16
,

Sangeeta Mangubhai

17
,

Elizabeth McLeod

18
,

Nyawira A. Muthiga

19
,

Josheena Naggea

20
,

Ravaka Ranaivoson

21
,

Amelia Wenger

22
,

Irfan Yulianto

23
&

Stacy D. Jupiter

24

Georgina G. Gurney

Georgina G. Gurney is a senior research fellow in environmental social science at the Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Australia.

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Emily S. Darling

Emily S. Darling is director, Coral Reef Conservation, Wildlife Conservation Society.

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Gabby N. Ahmadia

Gabby N. Ahmadia is director, Marine Conservation Science, Ocean Conservation, World Wildlife Fund.

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Vera N. Agostini

Vera N. Agostini is deputy director, Fisheries and Aquaculture Division, Food and Agriculture Organization of the United Nations.

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Natalie C. Ban

Natalie C. Ban is associate professor in environmental studies at the University of Victoria, Canada.

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Jessica Blythe

Jessica Blythe is assistant professor in environmental sustainability at Brock University, St Catharines, Canada.

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Joachim Claudet

Joachim Claudet is a senior researcher at the National Center for Scientific Research, CRIOBE, France.

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Graham Epstein

Graham Epstein is a postdoctoral research associate at the School of Politics, Security and International Affairs at the University of Central Florida, Orlando, USA.

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Estradivari

Estradivari is a researcher at the Leibniz Center for Tropical Marine Research (ZMT), Germany, and a conservation research manager, World Wildlife Fund Indonesia.

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Amber Himes-Cornell

Amber Himes-Cornell is a fisheries officer, Fisheries and Aquaculture Division, Food and Agricultural Organization of the United Nations.

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Harry D. Jonas

Harry D. Jonas is an international lawyer at Future Law, Kota Kinabalu, Malaysia, and co-chair of the IUCN WCPA Specialist Group on Other Effective Area-based Conservation Measures.

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Derek Armitage

Derek Armitage is a professor in the School of Environment, Resources and Sustainability, University of Waterloo, Canada.

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Stuart J. Campbell

Stuart J. Campbell is senior director, RARE Indonesia.

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Courtney Cox

Courtney Cox is senior director, Rare, Washington DC, USA.

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Whitney. R. Friedman

Whitney R. Friedman is a postdoctoral fellow at the University of California, Santa Barbara, USA.

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David Gill

David Gill is an assistant professor of marine science and conservation at Duke University, Durham, North Carolina, USA.

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Peni Lestari

Peni Lestari is a socioeconomic marine specialist, Wildlife Conservation Society.

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Sangeeta Mangubhai

Sangeeta Mangubhai is director, Fiji Program, Wildlife Conservation Society.

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Elizabeth McLeod

Elizabeth McLeod is global reef lead, The Nature Conservancy, Arlington, Virginia, USA.

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Nyawira A. Muthiga

Nyawira A. Muthiga is director, Marine Conservation Program, Kenya Program, Wildlife Conservation Society.

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Josheena Naggea

Josheena Naggea is a PhD candidate at Stanford University, California, USA, studying conservation in her home country of Mauritius.

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Ravaka Ranaivoson

Ravaka Ranaivoson is marine director, Madagascar Program, Wildlife Conservation Society.

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Amelia Wenger

Amelia Wenger is a research fellow in the School of Earth and environmental sciences at the University of Queensland, Brisbane, Australia, and a conservation scientist at the Wildlife Conservation Society.

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Irfan Yulianto

Irfan Yulianto is a researcher and lecturer at Institut Pertanian Bogor University, Indonesia, and a Senior Manager, Wildlife Conservation Society.

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Stacy D. Jupiter

Stacy D. Jupiter is Melanesia regional director at the Wildlife Conservation Society.

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Customary fishing-rights holders from Totoya Island, Fiji, marking a sacred reef area as a no-fishing zone.Credit: Keith Ellenbogen

Global support is growing for the 30 × 30 movement — a goal to conserve 30% of the planet by 2030. In May, the G7 group of wealthy nations endorsed the commitment to this target that had been made by more than 50 countries in January. It is likely to be the headline goal when parties to the Convention on Biological Diversity (CBD) meet to discuss the latest global conservation agreement in May 2022 in Kunming, China.So where do the sacred forests of Estonia or shipwrecks in North America’s Great Lakes come in? What do these share with managed fishing grounds in Fiji and bighorn-sheep hunting areas in Mexico? All have the potential to be recognized using a conservation policy tool called other effective area-based conservation measures, or OECMs. Together with protected areas — from Malaysia’s Taman Negara National Park to the Cerbère-Banyuls Marine Reserve in southern France — OECMs could help to achieve the 30% target.Devised in 2010 and defined in 2018, the OECM tool is little known outside specialist circles. Less than 1% of the world’s land and freshwater environments and less than 0.1% of marine areas are currently covered under this designation. Meanwhile, biodiversity is in free fall and protected areas alone can’t stem the loss. Both designations are among the international policy instruments being negotiated ahead of the CBD conference.We call on the CBD parties and the conservation community of policymakers, scientists, practitioners and donors to study and use OECMs more, alongside protected areas. This policy tool can advance equitable and effective conservation if CBD parties stay true to the convention’s intent to sustain biodiversity rather than ‘achieve’ area-based targets. But more groundwork must be laid to realize its potential.Improvements are needed in research, policy and practice. Local managers and CBD parties need better ways to assess whether potential OECMs contribute to sustaining biodiversity, so that areas are properly designated. The conservation community needs to develop processes to ensure that OECM recognition strengthens, rather than displaces, existing local governance. And researchers need to articulate the value of OECMs to encourage policymakers to use them.Bigger toolkit Protected areas have expanded rapidly in the past 10 years, and now cover 15.7% of the world’s land and fresh water, and 7.7% of the marine realm. Defined by the CBD as areas designated or regulated and managed for biodiversity conservation, they are an essential conservation approach. But some have failed to be equitable or effective: aligning biodiversity goals with local values, needs and governance can be difficult in some contexts1,2. This conflict can lead to inequities, non-compliance and poor biodiversity outcomes.
Indigenous rights vital to survival
OECMs can have an important and complementary role3. The tool recognizes managed areas that sustain biodiversity, irrespective of their objective. OECM recognition can support Indigenous and local communities in managing their lands and seas — be it for hunting, fishing or other cultural practices — while conserving nature. It opens up new conservation opportunities in landscapes where there is relatively light human usage, such as pastoralism with a low density of livestock. These regions make up nearly 56% of the world’s lands, and contain more Key Biodiversity Areas — sites of global important to biodiversity — than do remaining large wild areas4. So, management approaches that accommodate the ways people use landscapes and seascapes are crucial.Some managed areas do not safeguard biodiversity5. But there is a wealth of evidence suggesting that many do. For example, a study of the Peruvian Amazon found that Indigenous peoples’ territories were, on average, more effective than state-governed protected areas at preventing deforestation6. A review of 61 areas managed under territorial-use rights in fisheries in Chile found positive effects on biodiversity; some had levels of fish biomass and biodiversity that were comparable to those in a protected area that restricts all fishing7. And abandonment of agricultural management systems involving low-intensity farming methods in Europe — such as traditional haymaking in Romania — has been linked repeatedly to biodiversity loss8.Perhaps many of these could be recognized as OECMs (see ‘Conservation potential’). Doing so depends on the consent of the relevant governing bodies, and whether the managed area meets the CBD’s definition and criteria for OECMs, including demonstrated or expected biodiversity outcomes.

EquityOECMs can help to ensure that international conservation targets are legitimate to the many and diverse actors required to turn the tide on biodiversity loss.Too often, the costs of conservation are felt locally while many of the benefits are shared globally — from carbon sequestration to preserving genetic resources. For instance, rainforest conservation, including a protected area, in the Ankeniheny-Zahamena Corridor in Madagascar meant that local farmers of vanilla, cloves and rice bore opportunity costs representing 27–84% of their average annual household income. The protection scheme is intended to cut 10 million tonnes of carbon dioxide emissions over 10 years9.Such inequities can occur when protected areas do not prioritize local values and needs. Although protected areas can have multiple objectives, the widely followed guidance from the International Union for Conservation of Nature (IUCN) advises that nature conservation should retain priority over all other objectives. This can alienate people who manage areas for other reasons. Even in the instance of Indigenous Protected Areas in Australia, which have resulted in an array of social and biodiversity benefits, the IUCN definition can undermine Indigenous Australians’ conceptualization of humans as part of nature, which underpins their governance systems2. This stands in contrast to the Western world view of humans as distinct from nature — a concept that is embedded in the IUCN definition and conservation more generally2,3.
A spatial overview of the global importance of Indigenous lands for conservation
However, OECMs need not have conservation as an objective. This means that they can be used to recognize the contributions of a myriad of actors who manage areas that sustain nature, regardless of why they do so. Indigenous peoples, for instance, manage 37% of the world’s natural lands10 for many reasons, such as maintaining rights, harvesting and cultural identity2,10,11. Recognition of Indigenous territories as OECMs could help to overcome current challenges of insecure rights, insufficient funding and exclusion of these communities from decision-making12. For example, Indonesia has initiated revisions to its conservation laws to accommodate coastal OECMs, which could provide opportunities for Indigenous and local communities to gain legal recognition of their rights to use and manage fisheries.OECMs can thus ensure a more equitable approach to conservation decision-making. They enable the participation of those who govern areas that sustain biodiversity but who are currently not involved in decision-making. For example, fisheries-management organizations have rebuilt some fish stocks, contributing to biodiversity and wider ecosystem health, yet the fisheries and conservation sectors are often divided13. OECMs can foster cooperation between sectors, and encourage the participation of fisheries-management organizations in conservation decision-making.EffectivenessCollectively, alongside protected areas, OECMs can increase the effectiveness of the global conservation system in four key ways.First, they support management that is tailored to its context14, and aligned with local values, governance and traditional knowledge systems. This fosters the local leadership, support and compliance that are key to biodiversity benefits14. For example, in Mo’orea, French Polynesia, protected areas that restricted all fishing did not meet fishers’ needs, leading to non-compliance and relatively little change in the density and biomass of coral-reef fish15. Conversely, a management area in Labrador, Canada, implemented at the behest of crab fishers, maintained the fishery and increased the biomass of fish species such as Atlantic cod (Gadus morhua) and other, non-target species16. This area seems likely to meet the OECM criteria.

Estonia’s sacred groves are protected for their spiritual significance.Credit: Toomas Tuul/FOCUS/Universal Images Group via Getty

Second, OECMs, together with protected areas, can help to ensure a well-connected conservation network in which all elements of biodiversity are represented and in which ecological processes, such as species movements, are sustained. For instance, Kenya’s wildlife conservancies provide geographical bridges between protected areas for the movement of wildlife such as zebras, and have potential to be recognized as OECMs.Third, OECMs can increase the diversity of tools in the global conservation system. This bolsters the system’s resilience to social and biophysical shifts, including climate change14. Redundancy in governance arrangements can help to mitigate risks associated with the current reliance on government-led protected areas, which are vulnerable to shifts in national priorities. For example, in 2017, the Bears Ears National Monument, a protected area in Utah, was downsized by 85% to make way for oil and gas exploration under a former US presidential administration.Fourth, OECMs help to bring conservation outcomes into focus. A key criterion for official designation is demonstrated or expected biodiversity outcomes, such as the restoration of a crucial habitat. This is not the case for protected areas, where a focus on coverage has, in some cases, led to expansion with scant biodiversity gains4.Five steps Key concerns remain about the misuse of OECM recognition. CBD parties might use it to meet commitments without actually tackling biodiversity loss. For example, in 2017, Canada increased the marine area it planned to report almost sixfold, by reclassifying 51 fishery closures as OECMs17. This decision was criticized on the grounds of insufficient evidence that these areas sustain biodiversity. Another concern is that, despite the focus on equity, any attempts to influence local governance could be perceived as a ‘land grab’ or ‘sea grab’ by external actors such as national governments, foreigners or international organizations. For example, the establishment of some privately owned protected areas in southern Chile has been suggested to have involved coercion and intimidation of smallholder farmers.
Area-based conservation in the twenty-first century
The conservation community needs to take the following five steps to overcome these key challenges to using the OECM policy tool.Show that they work. The 2019 IUCN Guidelines for Recognizing and Reporting OECMs provide clear criteria for identifying managed areas that are suitable for a full assessment against the CBD’s definition. However, research is needed on how to meet the crucial criteria of demonstrated or expected in situ conservation of biodiversity. This is challenging and resource-intensive, especially because of the variety of actors involved. Ideas based in Western science might not align with the knowledge systems of all involved.Guidelines should build on existing approaches for evaluation, such as the IUCN Green List for Protected and Conserved Areas and the Indicators of Resilience in Socio-ecological Production Landscapes (SEPLs). They should include recent advances focused on outcomes18 and should be tailored to different types of managed area. To ensure that these are salient, credible and legitimate to those governing OECMs, they should be co-produced by groups such as rights holders, civil-society organizations, government and industry, as well as by academics from various disciplines. This transdisciplinary approach is growing rapidly, with examples ranging from management at the national level (such as New Zealand’s Sustainable Seas National Science Challenge) to the monitoring of coral reefs as social-ecological systems19.

Pastoral lands in Africa are often governed to maintain sustainable grazing.Credit: Steve Pastor

Strengthen existing local governance. Many rights holders have raised concerns that formal recognition of their managed areas for conservation might infringe their rights. For example, few communities in Fiji have had their fisheries-management areas recognized under national conservation laws, because that currently requires the communities to waive their customary rights20.Engaging with global conservation processes might also erode self-determination through the imposition of external world views2,3,12. Although OECMs open the door to recognizing diverse relations between humans and nature, it is crucial that the need for demonstrated or expected biodiversity outcomes does not diminish other priorities and values.OECM recognition must strengthen existing local governance, rather than displace or substantially alter it. This will require guidelines to be informed by principles of procedural equity and tailored to different types of managed area. Their development should draw on existing approaches such as the Australian Indigenous-led Healthy Country Planning and Our Knowledge, Our Way guidelines, which have underpinned engagement with the national carbon sequestration scheme11.Secure funding. Funding for recognizing and reporting OECMs should be made available to ensure costs are not a barrier or burden for under-resourced groups. A prominent role for OECMs in the next CBD agreement will help — this policy guides conservation investments from nations and donors.
Sixty years of tracking conservation progress using the World Database on Protected Areas
Importantly, the diversity of managed areas that OECMs encompass can provide funding opportunities beyond conventional conservation funders, whose resources for protected-area funding are already overstretched. Conservation practitioners should engage private sectors that manage areas that could be recognized as OECMs, and access funding earmarked for other priorities such as health and development. For example, the Watershed Interventions for Systems Health project in Fiji, which aims to reduce waterborne diseases using nature-based solutions, is supported by both conservation and public-health funding.Conservation donors and practitioners should co-design new funding strategies for OECMs with those governing these areas. This will help to ensure that local priorities are supported. For example, Coast Funds, a unique conservation trust fund, was developed by First Nations people in collaboration with conservation practitioners and the forestry industry to support stewardship of the Great Bear Rainforest and Haida Gwaii regions of British Columbia, Canada.Agree on metrics. The record of progress towards the CBD’s area-based target, the World Database on Protected Areas, assumes that all reported protected areas have biodiversity conservation as a main objective. But some CBD parties report areas that have other primary objectives, such as sustainable harvesting20. This leads to inaccurate accounting at the global level, and to misunderstanding of management actually occurring on the ground. Canada, among others, is developing legislation that demarcates protected areas and OECMs. But it is not clear whether all CBD parties will do the same.Policymakers need to agree on targets that are based on outcomes — not just coverage — for both OECMs and protected areas. These might include, for example, changes in the populations of multiple species relative to a reference point. In constructing these targets, the conservation community should be guided by the development and health sectors, which have long used outcome targets. For example, the United Nations Sustainable Development Goal 1.2 aims to reduce at least by half the proportion of people living in multidimensional, regionally-defined poverty by 2030. A common currency of outcomes could alleviate concerns that there is an uneven burden of proof for the OECM and protected-area tools. It could also prevent the misuse of either to meet targets based on area without actually sustaining biodiversity.Include OECMs in other environmental agreements. Addressing the interrelated global challenges of biodiversity loss, climate change and sustainability requires the coordination of policy across sectors. Right now, OECMs appear only in CBD policy. But they could contribute to the mandates of other intergovernmental initiatives. Policymakers should include OECMs alongside protected areas in international agreements such as the Sustainable Development Goals, new global climate agreements being negotiated under the UN convention on climate, and the emerging UN treaty on marine biodiversity in areas beyond national jurisdiction.New targets negotiated at the upcoming CBD meeting will set the global conservation agenda over the next decade. If the steps we outline here are implemented, OECMs could be central to the transformations needed for a sustainable future for the planet.

Nature 595, 646-649 (2021)
doi: https://doi.org/10.1038/d41586-021-02041-4

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Competing Interests
The authors declare no competing interests.

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Study sitesOur study sites are located on the Yatta Plateau in south-eastern Kenya. This region is characterized by dry savannahs. Annual rainfall (average: 810 mm) occurs during two periods, from March to May (average: 330 mm) and from October to January (average 480 mm) (c.f. Jaetzold et al.37). The commonest soil types are ferralsols and luvisols, which are of low fertility37. 97.1% of the human population in our study region depend on subsistence crop farming38, and the population has almost doubled in number from 1999 to 200938. Consequently, fallow periods for fields are omitted, which further decreases soil fertility, and increases pressure on pristine habitats.The dry savannah landscape is traversed by temporary (seasonal) rivers. These rivers are bordered by riparian vegetation, consisting of a diverse and unique plant community. However, this vegetation is frequently exploited for timber, charcoal and brick production39,40. The region is further affected by climate change, with an increase in rainfall variability and mean temperature37. These factors lower the reliability of agricultural production and food security, hence leading to severe destruction of pristine habitats.We selected two study sites, affected by different anthropogenic pressures, but which are subject to identical biotic and abiotic preconditions (including seasonality): Firstly, a highly degraded anthropogenic landscape along Nzeeu River, south of Kitui city. Secondly, a largely intact dryland environment along Kainaini River located near the university campus of the South Eastern Kenya University, north of Kitui city (Fig. 1). The landscape along Nzeeu River is densely populated by subsistence farmers. Thus, the original riparian and savannah vegetation has been mostly transformed into arable fields for the cultivation of maize, sorghum, peas, and mangos. Furthermore, the riparian vegetation, where it still exists, has largely been replaced by invasive exotic plant species (e.g. Lantana camara)12. The landscape of our second study site along Kainaini River represents a still largely intact riparian forest with adjoining dry savannahs. It remains mostly undisturbed, except for some moderate live-stock pasturing by nearby subsistence settlers.Butterfly assessmentsWe counted butterflies in both habitat types along line-transects, each 150 m long. We set 24 transects along each of the two rivers, with eight transects along the river bank, eight 250 m distant to the river, and another eight 500 m distant to the river (in total: 2 × 24 transects = 48 transects). The minimum distance between transects was at least 200 m, to minimize spatial autocorrelation. Exact GPS coordinates of each transect are given in Appendix S2.We recorded all butterflies encountered during transect counts (species, number of individuals of each species). Each transect was visited eight times during the dry season (August/September 2019) and eight times during the rainy season (January/February 2020). Data collection was performed between 9 a.m. and 4 p.m. Each butterfly individual within 5 m of the transect line (horizontally to vertically) was recorded by visual observation and, if needed, a butterfly net (see Pollard15, with modifications). While recording butterflies, the observers walked very slowly and spent about 15 min per transect. Species were identified either immediately while the butterfly was on the wing, or individuals were netted and then determined in the field. Individuals of species for which ad hoc identification was critical (e.g. many blues and skippers) were caught with the net, photographed (upper and under wing side) and released again. The photograph-based identification of these individuals was performed later using literature25. Apart from species and number of individuals per species, we recorded cloud cover during each transect walk (classified as: clear, slightly cloudy, mostly cloudy, overcast), exact time, and date. Field teams comprised two observers and one person making notes of all observations. Transects are displayed in Fig. 1. All butterfly data collected are compiled in Appendix S3.TraitsThe occurrence of a species in a specific environment strongly depends on its ecology, behaviour, and life-history41. Therefore, we considered these characteristics for each butterfly species recorded in the field. These trait data were compiled from Larsen25 and web-sites (e.g. www.gbif.org, www.lepiforum.de/non-eu.pl). We considered the following characteristics: wing span (mm), ratio length/width of the forewing (relative), ratio forewing length/thorax width (relative), geographic distribution (4 categories), savannah index (5 categories), forest index (5 categories), tree index (3 categories), wetness index (3 categories), habitat specialisation (3 categories), larval foodplant specialisation (3 categories), larval food plant type (dicotyledonous, monocotyledonous), and hemeroby index (4 categories). Detailed classifications are provided in Appendix S4.Habitat parametersHabitat structures impact species´ occurrence, abundances and community structures42. In our study, we considered habitat structures for each transect. Habitat parameters were recorded (counted and estimated) every 20 m along each transect. We estimated the following habitat parameters: Canopy cover (percentage of leaf cover vs. sky measured with the CanopeoApp); herb, shrub and tree cover (percentage coverage of each layer within a radius of 3 m); flowers on herbs, shrubs and trees (estimated within a radius of 3 m, and subsequently allocated to the classes 0, 1–10, 11–50, 51–100 and  > 100 flowers); occurrence of Lantana camara shrub, and exotic trees (estimated coverage within a radius of 3 m, and subsequently allocated to the classes 0 (no), 1 (rare), 2 (present) and 3 (dominant), respectively); and water availability (presence/absence) within a radius of 3 m. All raw data of habitat parameters are provided in Appendix S5.StatisticsWe first arranged the raw data in three matrices: a 71 × 14 species × trait matrix T, a 71 × 96 species × transect matrix M, and a 6 × 96 habitat characteristics × transect matrix H. Matrix multiplication of E = T−1MA−1, where A is the vector of total abundances in the transects, returned a matrix E of average trait expression in each transect.To answer the first research question, we compared species richness, abundances, and trait expression between the transects and used general linear modelling (glm) to detect differences in richness and trait expression with respect to the study sites (i.e. the two river systems with their different land-use patterns), season, distance from the rivers, as well as to environmental variables. Some of the habitat variables and trait expressions were highly positively correlated (Appendix S1). Consequently, the glm included only variables correlated by less than r = 0.7 (i.e. shrub cover, tree cover, habitat specialisation, savannah index, larval foodplant specialisation, and hemeroby).To infer differences in community structure between transects (second research question), we first calculated the two most dominant eigenvectors, which explained 91.5% and 3.5% of variance, of a principal components analysis of the M matrix. These eigenvectors cover differences in species composition between and within transects. We used glm and two-way Permanova to relate these differences to season, distance to river, and study sites (i.e. different land-use types in the two river systems). Additionally, we assessed the degree of β-diversity among sets of transects with the proportional turnover metric of Tuomisto43: (beta =1-frac{alpha }{gamma }); where α denotes the average species richness per transect and γ the corresponding total richness.To infer species spill-over effects from the riparian forests into the adjoining savannah (third research question), we calculated the Bray–Curtis similarities for three groups of transects within each season and study site. First, we compared average pairwise Bray–Curtis values between transects of intermediate and greater distance with the near-river transects within each study site. Second, we calculated the average Bray–Curtis similarities between all transects within each study site (2)—season (2)—distance class to river (3) combination. Third, we calculated the average within-transect Bray–Curtis similarity for the rainy season, to infer small scale compositional variability. The latter calculations were impossible for the dry season, due to the overall low number of recorded species. Calculations were done with Statistica 12. More

Sea urchins and experimental designSeven hundred small S. intermedius (31.9 ± 0.4 mm of test diameter, mean ± SD) were chosen from an aquaculture farm in Changhai County, Dalian (122° 63′ N, 39° 25′ E) on 23 July 2020. They were subsequently transported to the Key Laboratory of Mariculture and Stock Enhancement in North China’s Sea, Ministry of Agriculture and Rural Affairs at Dalian Ocean University (121° 56′ N, 38° 87′ E) and maintained in a fiberglass tank (a closed culture system, length × width × height: 150 × 100 × 60 cm) with aeration for 7 days to acclimatize to laboratory conditions. The kelp Saccharina japonica, which is the most common food used for S. intermedius culture58, was fed ad libitum under the neutral photoperiod (12 h light:12 h dark). One-half of the seawater was changed daily. Water temperature, pH and salinity were 22.6 ± 0.2 °C, 7.7 ± 0.3 and 30.7 ± 0.1 ‰ (Mean ± SD) according to the daily measurement using a portable water quality monitor (YSI Incorporated, OH, USA), respectively.The rearing space was defined as the ratio of culture volume to the number of sea urchins (cm3 ind−1). Rearing assemblage is the main factor being tested in this study. To simulate the currently used rearing assemblage in longline culture, 24 individuals were placed at plastic devices without layer divisions (length × width × height: 24.5 × 16.8 × 6 cm for culture volume; 25 holes of 0.5 cm diameter/100 cm2) as group A (the control group, 102.9 cm3 ind−1 of initial rearing space, Fig. 7a). To investigate whether multi-layer rearing assemblage improves the survival, food utilization and growth, 24 sea urchins were equally put into the cages where were evenly divided into three layers (8 sea urchins in each layer and length × width × height: 24.5 × 16.8 × 6 cm for each layer, 308.7 cm3 ind−1 of initial rearing space; 25 holes of 0.5 cm diameter/100 cm2; group B; Fig. 7b). Further, to evaluate whether eliminating interaction further contributes to the improvement of these commercially important traits of sea urchins in multi-layer rearing assemblage, 8 sea urchins were divided into eight divisions for each layer in the cages as group C (length × width × height: 8.3 × 5.9 × 6 cm for each division, 297.36 cm3 ind−1 of initial rearing space; 25 holes of 0.5 cm diameter/100 cm2; Fig. 7c). Each treatment had 8 replicates. All devices were placed in a fiberglass tank (length × width × height: 150 × 100 × 60 cm) and immersed in water for ~ 30 cm with aeration. They were easily disassembled for the experimental management.Figure 7Diagrams of the experimental cages used for the groups A (a), B (b) and C (c), the sea urchin with the spotting disease (d) and without the disease (e) and the devices used for measuring the Aristotle’s lantern reflex (f).Full size imageThe experimental period was about ~ 7 weeks (from 31 July 2020 to 20 September 2020) under the neutral photoperiod (12 h light: 12 h dark). The kelp, which was regularly collected in the intertidal waters at Heishijiao, Dalian (121° 58′ E, 38° 87′ N), was daily provided to sea urchins in abundance for all the groups. The remained kelp, feces and dead sea urchins were removed daily. One-half of the seawater was replaced daily by the fresh and filtered seawater which was pumped from the coast of Heishijiao, Dalian. Water temperature was not controlled, ranging from 22.2 to 24.5 °C (the natural seasonal cycle of increasing temperature during summer in the region). Water quality parameters were measured weekly as salinity 29.3 ± 0.6 ‰, pH 7.8 ± 0.2 (mean ± SD) using a portable water quality monitor (YSI Incorporated, OH, USA).To ensure the random sampling, sea urchins were taken out from the experimental device and placed in 24 plastic boxes (labeled from number 1 to number 24, length × width × height: 6 × 6 × 4 cm for each box). Individuals were chosen corresponding to the number (within 24) generated by the “sample” function in R studio (1.1.463). Sampling was re-conducted if the number corresponds to empty, dead or diseased sea urchins.Mortality and morbiditySpotting disease, which appears as spotting lesions with red, purple or blackish color on the test (Fig. 7d), is the most common lethal disease in S. intermedius aquaculture12. Sea urchin without disease is shown in Fig. 7e. Dead sea urchins were removed daily and the number of survivor and diseased sea urchins was recorded weekly for each cage during the experiment (N = 8).Food consumptionThe measurement of food consumption (g dry weight) was conducted once a week (24 h from Tuesday to Wednesday) (N = 8). The total supplied and remained diets were weighted wet by an electric balance (G & G Co., San Diego, USA) after the removal of the surface moisture. The dried weights of feces and samples of supplied and uneaten kelp were determined after 4 days at 80 °C in a convection oven (Yiheng Co., Shanghai, China).Food consumption was calculated as follows (revised from Hu et al.9 for being more concise):$${text{F}} = frac{{{text{A}}_{0} times frac{{{text{A}}_{1} }}{{{text{A}}_{2} }} – {text{B}}_{0} times frac{{{text{B}}_{1} }}{{{text{B}}_{2} }}}}{{text{N}}}$$F = dry food intake per sea urchin (g ind−1 day−1), A0 = wet weight of total supplied diets (g), B0 = wet weight of total uneaten diets (g), A1 = dried weight of sample supplied diets (g), A2 = wet weight of sample supplied diets (g), B1 = dry weight of sample uneaten diets (g), B2 = wet weight of sample uneaten diets (g), N = the number of sea urchins.GrowthTest diameter and lantern length were measured using a digital vernier caliper (Mahr Co., Ruhr, Germany). Body, lantern and gut were weighted wet using an electric balance (G & G Co., San Diego, USA). Test diameter and body weight were evaluated every Wednesday. The average value of the three individuals was considered as the trait value for each replicate (N = 8). Lantern length, wet lantern weight and wet gut weight were recorded in week 4 (29 August 2020) and week 7 (20 September 2020) (N = 8).Aristotle’s lantern reflexAristotle’s lantern reflex, which refers to one cycle from the opening to the closing of the teeth59, was measured using a simple device according to the method of Ding et al.38. There were small compartments (length × width × height: 4.8 × 5.6 × 4.5 cm) with a film (made by 3 g agar and 2 g kelp powder) on the bottom of the device38 (Fig. 7f). The frequency of Aristotle’s lantern reflex was counted within 5 min using a digital camera (Canon Co., Shenzhen, China) under the device in week 4 (29 August 2020) and week 7 (20 September 2020). The average value of all the 5 individuals was considered as Aristotle’s lantern reflex for each replicate (N = 8).5-HT concentrationThe 5-HT is a signaling molecule, playing an important role in regulating feeding behavior52. To evaluate whether 5-HT is involved in Aristotle’s lantern reflex, 5-HT concentration of muscle in lantern was measured for each treatment in week 4 and week 7. 5-HT concentration was considered as the average value of all the 3 healthy individuals for each replicate (N = 8).The concentration of 5-HT was measured using ELISA kits (Nanjing Jiancheng Bio-engineering Institute, Nanjing, China) according to the instructions of the manufacturer. After adding the enzyme-labeled antibody, the substrate became a colored product that was directly related to the amount of the substance tested. The concentrations of 5-HT were calculated by comparing the optical density (O.D.) value of the samples to the standard curve and calculated according to the following formula (according to the kit’s instructions):$${text{Y}} = frac{1}{{({text{a }} + {text{bx}}^{{text{c}}} )}}$$Y = the concentration of 5-HT (ng mL−1), x = the O.D. value of the samples, a = 0.00027, b = 0.12086, c = 1.36806.Pepsin activityPepsin is important for sea urchins to digest protein-rich algae40,60. Pepsin activity was analyzed using the pepsin kits (Nanjing Jiancheng Bio-engineering Institute, Nanjing, China) in week 4 and week 7, following the instructions of the manufacturer. The average value of all the 3 individuals was considered as the pepsin activity for each replicate (N = 8). The procedures include enzyme reaction and color development reaction39. The temperature of reaction was 37 °C and pepsin activities were counted as U mg protein−1. The formula of pepsin activity is shown as follows (according to the kit’s instructions):$${text{P}} = frac{{{text{M}}_{0} – {text{M}}_{1} }}{{{text{M}}_{2} – {text{M}}_{3} }} times frac{{{text{S}}_{0} }}{{{text{S}}_{1} }} times frac{{{text{V}}_{1} times {text{V}}_{2} }}{{{text{V}}_{3} }}$$P = pepsin activity (U/mg prot), M0 = the O.D. value of the sample, M1 = the O.D. value of comparison, M2 = the standard O.D. value, M3 = blank O.D. value, S0 = the standard concentration (50 μg mL−1), S1 = reaction time (10 min), V1 = total volume of reaction solution (0.64 mL), V2 = sample protein concentration (0.04 mL), V3 = sampling volume (mg prot/mL).Gut morphological examinationAfter sea urchins were dissected on week 4 and week 7, all gut tissue samples (~ 1 g for each sample) were fixed in Bouin’s solution (glacial acetic acid: formaldehyde: saturated picric acid solution = 1:5:15) according to the method of Wu et al.61. They were subsequently transferred for gradient dehydration, embedding, cutting, staining and observation62 (N = 24).Statistical analysisKolmogorov–Smirnov test and Levene test were used to analyze the normal distribution and homogeneity of the data, respectively. Rearing assemblage was set as the main factor in the one-way ANOVA with three levels: the control system without layer divisions (group A), a second system with divisions in the cages to simulate the three layers cages (group B) and a third system with individual divisions for each sea urchin (group C). One-way ANOVA was used to analyze the mortality (in weeks 3, 4, 5, 6, 7), morbidity (in weeks 3, 6, 7), food consumption (in weeks 2, 5, 7), test diameter (in weeks 1, 2, 3, 4, 5, 6), body weight (in weeks 1, 4, 5, 7), 5-HT, pepsin activity, lantern length, lantern weight and gut weight. Duncan multiple comparison analysis was performed when significant differences were found in the one-way ANOVA. Kruskal–Wallis test was carried out to compare the differences of mortality (weeks 1, 2), morbidity (weeks 1, 2, 4, 5), food consumption (weeks 1, 3, 4, 6), test diameter (week 7), body weight (weeks 2, 3, 6) and Aristotle’s lantern reflex, because of non-normal distribution and/or heterogeneity of variance. A non-parametric post-hoc test was carried out when significant differences were found in the Kruskal–Wallis test. All data analyses were performed using SPSS 19.0 statistical software. A probability level of P  More