A landscape view of Ascophyllum nodosum (L.) Le Jolis management and harvesting impacts in Southwestern Nova Scotia Canada

A landscape view of Ascophyllum nodosum (L.) Le Jolis management and harvesting impacts in Southwestern Nova Scotia Canada | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A landscape view of Ascophyllum nodosum (L.) Le Jolis management and harvesting impacts in Southwestern Nova Scotia Canada Glyn J. Sharp, Joshua T Sharp This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7745870/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The harvesting of Ascophyllum nodosum (L.) Le Jolis resources of Nova Scotia and New Brunswick Canada are regulated by area-based management since 1989. The Tidal Organics Inc harvesting company has five leases with responsibility to manage large 928.5 h to 76677.7 h of the coastline. A mechanical harvester was introduced to Nova Scotia by Tidal Organics with (Global Positioning System) GPS charts of daily harvesting to 3-5 m. Tracking and landing data provides a comprehensive landscape view of resource utilization. GPS technology with traditional biomass sampling biomass and remote sensing of bed areas defined exploitation rates from the scale of bays to sectors .9 -17.6 ha, to beds 2.33± .47 ha to targeted polygons ha, .09 ± .01ha and swath of the cutter head 02± .15 N=30. Optimally harvestable biomass in Lunenburg Bay was 59% of the total and 4.6% was un-harvestable. The beds targeted by the mechanical harvester were exploited at 8.77 ± 9.06 % N=30 of harvestable biomass. The mechanical harvester was selective at the scale of .25m 2 within the swath of the cutter head for A nodosum clumps, clump length, and shoots within clumps. Ascophyllum Landscape GPS Management Area Based Exploitation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction The Ascophyllum nodosum (L.) Le Jolis industry of the Canadian Maritimes began 63 years ago in southwestern Nova Scotia, an area of high abundance (Sharp 1986). The harvest began under a laissez faire management of the resource by allocation of exclusive leases to two companies (Chopin and Ugarte 2006). Independent harvesters operated freely within each lease to optimize their daily and seasonal income without exploitation limits (Sharp 1986). A dramatic increase in demand for raw material for alginate extraction and fertilizers began in 1985 (Chopin and Ugarte 2006). Area based management (ABM) was introduced by Fisheries and Oceans Canada (DFO) individual leases were divided into geographically defined sectors. (Sharp and Tremblay 1989). Sectors are units of shoreline, islands and shoals with boundaries defined by the DFO marine plants biologist, fully implemented by 1995 and adopted in regulations (NSDFA 1997). Landings and effort are reported and controlled at this geographic scale. Areas of sectors vary from .16 ha to 17.65 ha and annual harvests 30 to 300 t sector -1 (Unpublished data). Landing reports depend on weekly sector location reports from each harvester. The accumulated landings of each sector were weighed on arrival at the processing facility to 10 kg. Exploitation rates in NS are limited to a 20% maximum of harvestable biomass in a sector; New Brunswick has a limit of 17 % per sector (Chopin and Ugarte 2006). Until the quota for a sector is reached mechanical or manual harvesters were free to choose the portion of a sector to harvest. Individual harvesters optimize their daily harvest per unit effort within the limits of their harvesting equipment. Factors impacting the accessibility of beds within a sector include prevailing weather, wave exposure and the relief of the intertidal substrate. Both mechanical and manual harvesting techniques require A nodosum to be floating for cutting and gathering into a vessel (Sharp 1986, Sharp and Sharp 2024, Ugarte et al 2006). Ascophyllum nodosum dominates the mid to lower intertidal of Atlantic coast. Harvesters will work on both falling and rising tides vertically and move laterally depending on the abundance and continuity of the resource. Wind and wave direction, velocity and height can move a vessel within a tide cycle. All these factors result in a patchy distribution of exploitation with a bed and within a sector day to day. Habitat impacts are limited by both the type of gear, the level of effort and quota limits for each sector based on harvestable biomass assessment (Chopin and Ugarte 2006). The impact of harvesting methods and exploitation rates on population structure, habitat, and associated communities were evaluated within controlled experiments and small units of resource (Sharp 1986, Ang et al 1993, Lazo and Chapman 1993, Ugarte et al 2006, Rangely and Davis 2000, Schmit et al 2015). It was not possible to place this data in the context of landscape scale within a sector due to the lack of subsector geographical resolution. The introduction of new mechanical harvesting technology in 2017 along with daily tracking of the machine using GPS chart plotters has permitted sub sector and sub bed scale evaluation of impact and exploitation (Sharp and Sharp 2024). This work examined the distribution of mechanical harvesting exploitation rates and selectivity at the scale of a bay, the bed, the targeted area of the bed and the swath of the machine’s cutter. Methods Sector scale Harvestable biomass is the portion of the total biomass with potential to be selected for a commercial harvest. It is a subset of the total biomass estimated for a lease. The definition of harvestable biomass also includes the accessibility, and logistics of harvesting. These factors are determined by the type of harvesting equipment and the material handling techniques. Ultimately it is the cost per ton of obtaining the raw material which will determine what portion of the total biomass is commercial. Portions of the resource at the outer limits of a bay or those existing in very small amounts in areas of wave sheltered areas are normally not economical to access. The amount of biomass accessible is related to the tide height and slope of the shore steeply sloping shorelines have the least area of floating canopy. Wave exposed shorelines are less likely to be accessible during the harvest season related to prevailing wind and wave height. If travel to and from these sites require passage past headlands open to ocean surge normally excludes these sites from harvests for safety reasons. The relief of the intertidal substrate will impact all methods of harvesting. Coastal areas with large boulders (≥2m) are places a mechanical harvester can become stranded on a dropping tide. Weather is an important factor in safely harvesting and logistics. The number calm days available to reach exposed to semi exposed coastline are limited. The distance from landing sites determines the travel time and the marine infrastructure impacts unloading times The continuity of biomass is a factor affecting the catch or harvest per unit effort (HPUE), t h-1or t tide cycle -1 . Areas with biomass discontinuity will vary in potential HPUE depending on the type of technology utilized for the harvest. Five factors were used to classify sectors in Lunenburg Bay to classify sectors; Un-harvestable biomass: shoreline slope greater than 50 0 , substrate relief ≥2m, wave exposure open angle to unlimited wave fetch greater than 60 0 , point sources of pollution, moderately harvestable: biomass ≤ 6 kg m -2 , biomass cover less than 30%; optimally harvestable all other biomass. Exploitation rates Exploitation rates within the swath of the harvester’s track, the targeted polygon in the bed, the bed were calculated for 30 bags of harvest chosen for single bag tracking in the commercial harvests of 9 sectors. Swath: Tracks of the harvesting machine were recorded for the distance and location to fill 30 individually labeled net bags subsequently weighed at the processing site .53 ± 71t N= 30. The track of the harvesting vessel was recorded every 30 sec with a resolution of 3-4 m with a Raymarine Elements tm chart plotter with a resolution of 3-4 m (Fig 1) . The exploitation rate was calculated as landing t ha -1 as percentage of the average total biomass in each area: the swath of the cutter head (.46 * track m) * 10000) = ha, the polygon ha and the bed ha including the associated polygon. Average harvestable biomass within the machine’s swath, the area of the targeted polygon and the bed was derived from annual ground truth surveys of commercially harvested A nodosum beds in 9 sectors in this study in May to June 2018 to 2024. Horizontal transects of 20 to 30 m long were placed in the center of the A nodosum zone .25m -2 quadrats were placed at 2 -4 m intervals. All fucoid biomass was removed above 20cm. Ascophyllum nodosum was separated from fucoid species and wet weight recorded to .05 kg. The average biomass per hectare was 119 ± 28.4 t ha -1 (N= 956). Polygon: The area of impact within the bed was delineated by the maximum limits of the tracks both vertically and horizontally within individual beds. The area of encompassed tracks were termed polygons. The area of each polygon was calculated with the field calculator function of QGIS. (Fig 1). Bed: The area of the bed impacted by harvesting activity was delimited by a perpendicular line drawn from the lowest limit of A nodosum distribution to the upper limit. The lateral boundaries were fixed by the associated tracks (Fig 1). harvesting intensity within tracks Transects (30 to 60m long); .25 m 2 quadrats were placed every 4 to 6 m in the harvested polygon of the bed (N=22). The total number of A nodosum clumps (assemblage of shoots attached to a single holdfast) in each quadrat were examined for evidence of harvest indicated by freshly severed tissues. The index of harvest intensity was the number of clumps .25 m -2 with any evidence of harvest / total number of clumps .25m -2 . Cutting height Immediately after mechanical harvesting in three sectors 20 m transects were placed in the center of targeted polygons; .25 m 2 quadrats were placed at 2 m intervals. All clumps of A nodosum length were measured to 1 cm and based on evidence of freshly cut tissue were classified as cut or uncut in each quadrat. Shoots Thirty A nodosum clumps with evidence of harvest were sampled in T1 post-harvest 2024 were dissected to separate shoots with evidence of cutting from uncut shoots (N= 1502). The length of each shoot in the clump was measured to 5 cm. Results Sector Scale Lunenburg harbour has 12 sectors designated for A nodosum resource management (Fig 2). However, only 5 of these sectors have optimal commercially harvestable resources (Fig 2). Fifty-nine percent of the biomass in Lunenburg Bay was optimally harvestable. Un-harvestable biomass was 4.6 % of total biomass and moderately harvestable was 37.4 % of total biomass. The total biomass of Lunenburg Bay is 3100 t. At an exploitation rate of 20% the annual harvest would be 600t; 377 t are optimal. At a maximum 20 % exploitation rate per year within optimal sectors the annual exploitation rate in Lunenburg Bay is 12.5%. Sub sector scale area Average area of the swath, polygon and bed was .02± .15 ha, .09 ± .01ha 2.33± .47 ha (N=30) respectively (Fig 3). The limits of the track determine the area of the polygon and the area of the targeted bed. The correlation was significant p < .001 Pearson’s r .809. Exploitation rate Exploitation rate based on the average harvest, harvestable biomass and track length decreased as the area increased from the swath to the polygon, and the bed 69.18 ± 68 %, 46.56 ± 53.00 %,8.77± 9.06 % respectively (Fig 4). The exploitation rate exponentially increased with the decrease in the area targeted by the machine (Fig 5). The inflection occurred at .01 ha. (Fig 5). The yield from each area was constant in this calculation; the exploitation rate represents the concentration of harvesting effort. Harvesting intensity The proportion of individual A nodosum clumps contacted by the cutter head within a .25 m 2 is a measure of intensity of cutting within its swath. The cutter head contacted all the clumps within .25 m -2 quadrats 3/22 samples distributed evenly over 84 m (Fig 6). The average intensity of cutting was .49 ±.21 clumps .25m -2 . Clump cutting height The height A. nodosum clumps are cut above the substrate reflects the degree of selectivity of the mechanical cutter head. Post harvest mechanical measurement of cut height in clumps from 2020 to 2022 commercial harvests from four areas averaged 64.4 to 93.4 cm range 37-212, N=1054. The proportion of cut and uncut clump total length in the swath reflected the selectivity of the machine’s cutter head (Fig 7). Clumps with evidence of recent cutting the mode was 50-75 cm versus 25- 50 cm length of uncut clumps (Fig 7). Shoots Contact of the cutter head with an A nodosum clump does not sever all shoots in a clump. The incidence of cut shoots within clumps with evidence of harvest averaged .25 ± .14 Range .05 to .68, (N= 1502) shoots (Fig 8). Discussion The ability to define the targeted harvest areas (polygons) enhances area-based management providing a plot of annual harvest at a sub sector level. The relationship between exploitation rate and the area of a polygon is to a degree a reflection of the limitations of the chart plotter. The description of a swath is a simplification of the movement of the harvester within a bed. The chart plotter is tracking the vessels movements every 30 seconds at a resolution of 3–5 m. When the operator moves the vessel laterally less than 5 m and within 30 sec the chart plotter does not record the distance. This limit of track resolution impacts the calculation of exploitation rate as the targeted area is less than 100 m 2 . Consequently, the calculated exploitation rates are generally overstated at this scale. Despite this limitation exploitation rates within the bed, one geographical scale above the polygon resulted in a maximum exploitation rate of 22%. The average commercial exploitation rate of summed polygons in 7 sectors harvesting 636 t in 2022 was 36.4 ± 10.9% (Sharp and Sharp 2024 ) The pattern of harvest within beds does not result in a clear cut of biomass or a homogenous exploitation rate within targeted portions of the beds. The operator selects portion of the beds optimal for economic return. The characteristics of the machine’s cutter head selects for the distal portions of individual clumps. The calculation of exploitation rates in this study was based on constants derived from averages of harvestable standing crop. Variation of biomass and distribution is related to both the harvest per unit effort and the harvesting strategies of the machine operator. The operator is paid a tonnage incentive and will choose to target the portion of the floating canopy providing a minimum kg h − 1 and kg tide − 1 . Operational limitations of the vessel result in the selection of beds within a sector by the operator to obtain an optimal harvest rate. Wind velocity, wave height tide level, distance from landing sites will impact on the location and degree of exploitation. The cutter head design and mode of cutting and gathering results in the characteristics of the post-harvest A nodosum population and the habitat structure. The cutter head does not cut all the shoots of a clump at one height related to the surrounding collar; a combination of suction and forward movement of the cutter head and the depth of the water feed the floating distal portions of shoots within the clump into the cutter head at various heights. The cutter tends to cut horizontally the shoots suctioned into the cutter head. Despite the high proportion of the polygon swept by the cutter head not all clumps are contacted by the cutter head. The high density of shoots in clumps with lateral and primary apices un-truncated allow recovery of biomass. The cutting height is affected by the length distribution of the population as well as the relief of the substrate and the selectivity of the cutter head and machine operator. Boulder substrate prevents the cutter head from reaching the bottom compared to a less complicated bedrock or small rock shoreline. The cutter head operated under these limitations was extremely selective for length of clumps and within clumps for length of shoots. There was no clear cut above the scale of .25m 2 in a polygon or bed nor do all clumps within .25m 2 have all shoots cut. The incidence of cut shoots within clumps is the final scale of exploitation. Most shoots are left untruncated and their growing tips continue to contribute to the productivity of the bed. The selectivity for longer clumps and shoots combined with the vertical distribution of biomass in clumps allows the removal of biomass with a low impact on the clump’s ability to recover from the harvest. The degree of habitat impacts at sub sector scale is very dependent on the intensity of harvesting within the bed and ultimately on the changes in assemblages of A nodosum clumps and shoots within a clump. Ascophyllum nodosum populations in southwestern Nova Scotia have sustained annual harvests for the past 64 years exceeding 20000 t yr-1 in 28 of the last 34 years. Harvest technology has changed several times between manual and mechanical techniques (Chopin and Ugarte 2006 ). Area based management has brought control of exploitation within sectors. Economic and logistical limits are factors selecting sectors for harvest and the portion of the beds targeted for harvest. Long term monitoring of population structure and biomass in targeted parts of the A nodosum resource during decades of commercial exploitation have not found significant changes (Lauzon-Guay et al 2021a , Lauzon-Guay et al 2021b , Lauzon-Guay et al 2023 . An issue of concern due to habitat impacts at landscape scale is fragmentation of the habitat and its impact on biodiversity (Yeager et al 2020 ). A patchy harvest can divide A nodosum beds into smaller units for the short and medium term as the population recovers from cutting a portion of the canopy. A further analysis of the spatial distribution of tracks within beds can potentially provide a measure of degree and extent fragmentation and patchiness caused by harvests. Declarations Funding This study was fully funded by Scotia Garden Seafood 112 Water Street Yarmouth NS. Competing Interests The corresponding author G Sharp is the sole proprietor of KCME Inc a consulting company. His company provides third party resource management and development research advisory services to seaweed buying and processing companies. Past clients have included Acadian SeaPlants Ltd, Nunavik Biosciences, Thorverk Iceland and Tidal Organics Inc. The co-author Joshua Sharp is a full-time employee of Tidal Organics Ltd. Data All data has been collected by accepted field methodology and is available in excel. Analysis was completed with open QGIS and MaxStat software. Author Contributions The corresponding author G Sharp and co-author J Sharp jointly contributed to study conception and design. Material and data collection was performed by J Sharp, data analysis was completed by G Sharp. Figure 1 3 4 were created by G Sharp, Figure 2 by J Sharp References Ang PO, Sharp GJ, Semple RE (1993) Changes in the population structure of Ascophyllum nodosum (L.) Le Jolis due to mechanical harvesting Hydrobiologica 261:321-326. Chopin T, Ugarte R (2006) The seaweed resource of eastern Canada in Critchley AT, Ohno M, Largo DB (eds) World Seaweed Resources: 46 p. DVD -ROM. ETI BioInformatics Amsterdam ISBN: 90 75000 80 4. Cousens R (1984) Estimation of annual production by the intertidal brown alga Ascophyllum nodosum (L.) Le Jolis Bot Mar 27:217-227 Lauzon-Guay JS, Ugarte RA, Morse BL, Robertson CA Jour Appl Phyco 2021a 33:1695–1708 Lauzon-Guay, JS., Ugarte,R, Morse, BL & Robertson C 2021b. Biomass and height of Ascophyllum nodosum after two decades of continuous commercial harvesting in eastern Canada. J Appl Phyco https://doi.org/10.1007/s10811-021-02427-x. Lauzon‑Guay JS, Feibel A, Morse BL, Ugarte RA (2023) Morphology of Ascophyllum nodosum in relation to commercial harvesting in New Brunswick, Canada J App Phyco 35:2371–2381 Lazo L, Chapman ARO (1993) Components of crowding in a modular seaweed: sorting through the contradictions Mar Ecol Prog Ser 174:257-267. NSDFA (1997) Rock Weed Regulations (RWR) S.N.S. Part VI (Sea Plants Harvesting) of the Fisheries and Coastal Resources Act. Chapter 25, Acts of 1996 and (to date) the Sea Plants Harvesting Regulations of the Fisheries and Coastal Resources Act, 1989, Chapter 416. Rangely R, Davis J (2000) Management of low trophic level fisheries in the face of uncertainty Marine Huntsman Marine Science Centre Occasional Report 00/1 p 94. Sharp GJ (1986) Ascophyllum nodosum and its harvesting in eastern Canada, in Case Studies of Seven Commercial Seaweed Resources, FAO Fisheries Technical Paper 281. Rome, Italy: Food and Agriculture Organization of the United Nations pp 3-48. Sharp GJ, Trembay D (1989). An assessment of Ascophyllum nodosum resources in Scotia Fundy CAFSAC Res. Doc. 89/1 p 19. Sharp GJ, Ang P, MacKinnon D (1994) Rockweed ( Ascophyllum nodosum ) (L.) Le Jolis harvesting in Nova Scotia: its socioeconomic and biological implications for coastal zone management. Proc Coastal Zone Canada 94: 1632-1644. Sharp GJ, Sharp JT (2024) Estimating Ascophyllum nodosum (L.) Le Jolis harvesting impacts using GPS Tracking of mechanical harvesters in Nova Scotia, Canada. J Appl Phycol 36: 605–610. Ugarte, R, Sharp G (2001) A new approach to seaweed management in eastern Canada: the case of Ascophyllum nodosum Cah. Biol. Mar. 42:63-70. Ugarte R, Sharp GJ, Moore B, (2006) Changes in the brown seaweed Ascophyllum nodosum (L.) Le Jol. plant morphology and biomass produced by cutter rake harvests in southern New Brunswick, Canada J Appl Phycol 18:351-359 Ugarte, R., Sharp, G. (2012) Management and Production of the brown algae Ascophyllum nodosum in the Canadian Maritimes J. Appl. Phycol 24: 409- 416. Schmidt AL, Coll M, Romanuk T, Lotze HK (2015) Ecosystem structure and services in eelgrass Zostera marina and rockweed Ascophyllum nodosum habitats Mar Ecol Prog Ser 437: 51–68. Yeager LA, Estrada J, Holt K, Keyser S, Olke TA (2020) Are Habitat Fragmentation Effects Stronger in Marine Systems? A Review and Meta-analysis Current Landscape Ecology Reports (2020) 5:58-67 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7745870","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":528880882,"identity":"c1a82c17-37be-461a-9906-0f36e2c044a4","order_by":0,"name":"Glyn J. 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1","display":"","copyAsset":false,"role":"figure","size":765537,"visible":true,"origin":"","legend":"\u003cp\u003elandscape scales of harvesting, pink line: track of the harvesting machine, yellow line: polygon drawn around the limits of the tracks, white line: the portion the bed targeted, red line: the bed.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7745870/v1/1fcdd5c56ce8858865908fc6.png"},{"id":93661362,"identity":"c08118d6-8d56-4d44-b7cd-c206b497c0f4","added_by":"auto","created_at":"2025-10-16 08:13:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":392289,"visible":true,"origin":"","legend":"\u003cp\u003eClassification of harvestability of sectors in Lunenburg Bay. Red: not harvestable; orange: moderate harvestable; green: optimal biomass for harvesting.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7745870/v1/3c2e24107de3515a56b997cf.png"},{"id":93661360,"identity":"e92588ca-4f78-4ddd-b212-5bc45bc86aad","added_by":"auto","created_at":"2025-10-16 08:13:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17156,"visible":true,"origin":"","legend":"\u003cp\u003eWhisker plot of the distribution of area data for the swath of the cutter head, the bounded targeted polygon, and the area of beds targeted.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7745870/v1/bd6afd25e997ddb052f34506.png"},{"id":93661745,"identity":"95a3f221-f917-4bd0-8798-64a559a4e551","added_by":"auto","created_at":"2025-10-16 08:21:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":17530,"visible":true,"origin":"","legend":"\u003cp\u003eWhisker plot of the distribution of exploitation rates within the swath of the cutter head, polygon and bounded bed.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7745870/v1/dff417adb1ff03f99779e933.png"},{"id":93661361,"identity":"c23fb4c0-c796-4265-aa72-25e40a81f666","added_by":"auto","created_at":"2025-10-16 08:13:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":19275,"visible":true,"origin":"","legend":"\u003cp\u003ethe relationship between exploitation rate in 30 \u003cem\u003eA nodosum\u003c/em\u003e beds and area ha of beds\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7745870/v1/930e6d3617975a47b85af11b.png"},{"id":93663165,"identity":"601eb7fa-4234-47ca-abfb-a12d6a3c8a8f","added_by":"auto","created_at":"2025-10-16 08:37:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":53068,"visible":true,"origin":"","legend":"\u003cp\u003eThe distribution of harvest along impact a transect set in the middle of a harvested polygon measured as a ratio of \u003cem\u003eA nodosum\u003c/em\u003e clumps with cut shoots of the total clump density within .25m\u003csup\u003e2\u003c/sup\u003e at 4m intervals within Sector LC 36.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7745870/v1/435aef4903a66288f936304f.png"},{"id":93662899,"identity":"c0256e3b-f4e5-4283-8f9d-284a8e4a7a59","added_by":"auto","created_at":"2025-10-16 08:29:34","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":18362,"visible":true,"origin":"","legend":"\u003cp\u003eThe length distribution of cut and uncut \u003cem\u003eA nodosum\u003c/em\u003eclumps in the population of a mechanically harvested \u003cem\u003eA nodosum\u003c/em\u003e bed in Liverpool 2022 (N= 565)\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7745870/v1/767a664702812fa957ef97fd.png"},{"id":93662898,"identity":"68c21f63-a341-48a0-9ef5-4efcf51f2618","added_by":"auto","created_at":"2025-10-16 08:29:34","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":14650,"visible":true,"origin":"","legend":"\u003cp\u003eWhisker plot the number of cut and uncut shoots in \u003cem\u003eA nodosum\u003c/em\u003e clumps contacted by the cutter head T1 2024 post-harvest\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7745870/v1/13f01f4e921a06a2964cac6a.png"},{"id":97378938,"identity":"b6eba00c-65cd-46b3-b4f3-b3414537a694","added_by":"auto","created_at":"2025-12-03 17:23:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2029062,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7745870/v1/7d5a98fa-1ab3-4ad0-9441-eb8cd76fa981.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A landscape view of Ascophyllum nodosum (L.) Le Jolis management and harvesting impacts in Southwestern Nova Scotia Canada","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe \u003cem\u003eAscophyllum nodosum (L.)\u003c/em\u003e \u003cem\u003eLe Jolis\u003c/em\u003e industry of the Canadian Maritimes began 63 years ago in southwestern Nova Scotia, an area of high abundance (Sharp 1986). \u0026nbsp;The harvest began under a laissez faire management of the resource by allocation of exclusive leases to two companies (Chopin and Ugarte 2006). Independent harvesters operated freely within each lease to optimize their daily and seasonal income without exploitation limits (Sharp 1986). A dramatic increase in demand for raw material for alginate extraction and fertilizers began in 1985 (Chopin and Ugarte 2006). Area based management (ABM) was introduced by Fisheries and Oceans Canada (DFO) individual leases were divided into geographically defined sectors. (Sharp and Tremblay 1989). Sectors are units of shoreline, islands and shoals with boundaries defined by the DFO marine plants biologist, fully implemented by 1995 and adopted in regulations (NSDFA 1997). Landings and effort are reported and controlled at this geographic scale.\u0026nbsp;Areas of sectors vary from .16 ha to 17.65 ha and annual harvests 30 to 300 t sector\u003csup\u003e-1\u003c/sup\u003e (Unpublished data). \u0026nbsp;Landing reports depend on weekly sector location reports from each harvester. The accumulated landings of each sector were weighed on arrival at the processing facility to 10 kg. Exploitation rates in NS are limited to a 20% maximum of harvestable biomass in a sector; New Brunswick has a limit of 17 % per sector\u0026nbsp;(Chopin and Ugarte 2006). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUntil the quota for a sector is reached mechanical or manual harvesters were free to choose the portion of a sector to harvest. Individual harvesters optimize their daily harvest per unit effort within the limits of their harvesting equipment. \u0026nbsp;Factors impacting the accessibility of beds within a sector include prevailing weather, wave exposure and the relief of the intertidal substrate. Both mechanical and manual harvesting techniques require \u003cem\u003eA nodosum\u003c/em\u003e to be floating for cutting and gathering into a vessel (Sharp 1986, Sharp and Sharp 2024, Ugarte et al 2006). \u0026nbsp; \u003cem\u003eAscophyllum nodosum\u003c/em\u003e dominates the mid to lower intertidal of Atlantic coast. Harvesters will work on both falling and rising tides vertically and move laterally depending on the abundance and continuity of the resource. Wind and wave direction, velocity and height can move a vessel within a tide cycle. All these factors result in a patchy distribution of exploitation with a bed and within a sector day to day.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHabitat impacts are limited by both the type of gear, the level of effort and quota limits for each sector based on harvestable biomass assessment (Chopin and Ugarte 2006). The impact of harvesting methods and exploitation rates on population structure, habitat, and associated communities were evaluated within controlled experiments and small units of resource (Sharp 1986, Ang et al 1993, Lazo and Chapman 1993, Ugarte et al 2006, Rangely and Davis 2000, Schmit et al 2015). It was not possible to place this data in the context of landscape scale within a sector due to the lack of subsector geographical resolution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe introduction of new mechanical harvesting technology in 2017 along with daily tracking of the machine using GPS chart plotters has permitted sub sector and sub bed scale evaluation of impact and exploitation (Sharp and Sharp 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work examined the distribution of mechanical harvesting exploitation rates and selectivity at the scale of a bay, the bed, the targeted area of the bed and the swath of the machine\u0026rsquo;s cutter. \u0026nbsp;\u003c/p\u003e"},{"header":"Methods ","content":"\u003cp\u003eSector scale\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHarvestable biomass is the portion of the total biomass with potential to be selected for a commercial harvest. It is a subset of the total biomass estimated for a lease. The definition of harvestable biomass also includes the accessibility, and logistics of harvesting. These factors are determined by the type of harvesting equipment and the material handling techniques. Ultimately it is the cost per ton of obtaining the raw material which will determine what portion of the total biomass is commercial. Portions of the resource at the outer limits of a bay or those existing in very small amounts in areas of wave sheltered areas are normally not economical to access. The amount of biomass accessible is related to the tide height and slope of the shore steeply sloping shorelines have the least area of floating canopy. Wave exposed shorelines are less likely to be accessible during the harvest season related to prevailing wind and wave height. If travel to and from these sites require passage past headlands open to ocean surge normally excludes these sites from harvests for safety reasons.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The relief of the intertidal substrate will impact all methods of harvesting. Coastal areas with large boulders (\u0026ge;2m) are places a mechanical harvester can become stranded on a dropping tide. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWeather is an important factor in safely harvesting and logistics. The number calm days available to reach exposed to semi exposed coastline are limited. The distance from landing sites determines the travel time and the marine infrastructure impacts unloading times\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe continuity of biomass is a factor affecting the catch or harvest per unit effort (HPUE), t h-1or t tide cycle\u003csup\u003e-1\u003c/sup\u003e. \u0026nbsp;Areas with biomass discontinuity will vary in potential HPUE depending on the type of technology utilized for the harvest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFive factors were used to classify sectors in Lunenburg Bay to classify sectors; Un-harvestable biomass: \u0026nbsp;shoreline slope greater than 50\u003csup\u003e0\u003c/sup\u003e, substrate relief \u0026ge;2m, wave exposure open angle to unlimited wave fetch greater than 60\u003csup\u003e0\u003c/sup\u003e, point sources of pollution, moderately harvestable: biomass \u003cu\u003e\u0026le;\u0026nbsp;\u003c/u\u003e6 kg m\u003csup\u003e-2\u003c/sup\u003e, biomass cover less than 30%; optimally harvestable all other biomass.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExploitation rates\u003c/p\u003e\n\u003cp\u003eExploitation rates within the swath of the harvester\u0026rsquo;s track, the targeted polygon in the bed, the bed were calculated for 30 bags of harvest chosen for single bag tracking in the commercial harvests of 9 sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSwath:\u0026nbsp;Tracks of the harvesting machine were recorded for the distance and location to fill 30 individually labeled net bags subsequently weighed at the processing site .53 \u0026plusmn; 71t N= 30.\u0026nbsp;The track of the harvesting vessel was recorded every 30 sec with a resolution of 3-4 m with a Raymarine Elements\u003csup\u003etm\u003c/sup\u003e chart plotter with a resolution of 3-4 m (Fig 1)\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe exploitation rate was calculated as landing t ha\u003csup\u003e-1\u003c/sup\u003e as percentage of the average total biomass in each area: the swath of the cutter head (.46 * track m) * 10000) = ha, the polygon ha and the bed ha including the associated polygon. \u0026nbsp;Average harvestable biomass within the machine\u0026rsquo;s swath, the area of the targeted polygon and the bed was derived from annual ground truth surveys of commercially harvested A nodosum beds in 9 sectors in this study in May to June 2018 to 2024. Horizontal transects of 20 to 30 m long were placed in the center of the A nodosum zone .25m\u003csup\u003e-2\u003c/sup\u003e quadrats were placed at 2 -4 m intervals. All fucoid biomass was removed above 20cm. \u0026nbsp;\u003cem\u003eAscophyllum nodosum\u003c/em\u003e was separated from fucoid species and wet weight recorded to .05 kg. The average biomass per hectare was 119 \u0026plusmn; 28.4 t ha\u003csup\u003e-1\u003c/sup\u003e (N= 956). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePolygon: The area of impact within the bed was delineated by the maximum limits of the tracks both vertically and horizontally within individual beds. The area of encompassed tracks were termed polygons.\u0026nbsp;The area of each polygon was calculated with the field calculator function of QGIS.\u0026nbsp;(Fig 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBed: The area of the bed impacted by harvesting activity was delimited by a perpendicular line drawn from the lowest limit of \u003cem\u003eA nodosum\u003c/em\u003e distribution to the upper limit. The lateral boundaries were fixed by the associated tracks (Fig 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eharvesting intensity within tracks\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTransects (30 to 60m long); .25 m\u003csup\u003e2\u003c/sup\u003e quadrats were placed every 4 to 6 m in the harvested polygon of the bed (N=22). The total number of \u003cem\u003eA nodosum\u003c/em\u003e clumps (assemblage of shoots attached to a single holdfast) in each quadrat were examined for evidence of harvest indicated by freshly severed tissues. \u0026nbsp;The index of harvest intensity was the number of clumps .25 m\u003csup\u003e-2\u003c/sup\u003e with any evidence of harvest / total number of clumps .25m\u003csup\u003e-2\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eCutting height\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eImmediately after mechanical harvesting in three sectors 20 m transects were placed in the center of targeted polygons; .25 m\u003csup\u003e2\u003c/sup\u003e quadrats were placed at 2 m intervals. All clumps of \u003cem\u003eA nodosum\u003c/em\u003e length were measured to 1 cm and based on evidence of freshly cut tissue were classified as cut or uncut in each quadrat.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eShoots\u003c/p\u003e\n\u003cp\u003eThirty \u003cem\u003eA nodosum\u003c/em\u003e clumps with evidence of harvest were sampled in T1 post-harvest 2024 were dissected to separate shoots with evidence of cutting from uncut shoots (N= 1502). The length of each shoot in the clump was measured to 5 cm.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eSector Scale\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLunenburg harbour has 12 sectors designated for \u003cem\u003eA nodosum\u003c/em\u003e resource management (Fig 2). \u0026nbsp;However, only 5 of these sectors have optimal commercially harvestable resources (Fig 2). Fifty-nine percent of the biomass in Lunenburg Bay was optimally harvestable. Un-harvestable biomass was 4.6 % of total biomass and moderately harvestable was 37.4 % of total biomass. The total biomass of Lunenburg Bay is 3100 t. At an exploitation rate of 20% the annual harvest would be 600t; 377 t are optimal. At a maximum 20 % exploitation rate per year within optimal sectors the annual exploitation rate in Lunenburg Bay is 12.5%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSub sector scale\u0026nbsp;\u003c/p\u003e\n\u003cp\u003earea\u003c/p\u003e\n\u003cp\u003eAverage area of the swath, polygon and bed was .02\u0026plusmn; .15 ha, .09 \u0026plusmn; .01ha 2.33\u0026plusmn; .47 ha (N=30) respectively (Fig 3). The limits of the track determine the area of the polygon and the area of the targeted bed. The correlation was significant p \u0026lt; .001 Pearson\u0026rsquo;s r .809.\u003c/p\u003e\n\u003cp\u003eExploitation rate\u003c/p\u003e\n\u003cp\u003eExploitation rate based on the average harvest, harvestable biomass and track length decreased as the area increased from the swath to the polygon, and the bed 69.18 \u0026plusmn; 68 %, 46.56 \u0026plusmn; 53.00 %,8.77\u0026plusmn; 9.06 % respectively (Fig 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe exploitation rate exponentially increased with the decrease in the area targeted by the machine (Fig 5). The inflection occurred at .01 ha. (Fig 5). The yield from each area was constant in this calculation; the exploitation rate represents the concentration of harvesting effort.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHarvesting intensity\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe proportion of individual \u003cem\u003eA nodosum\u003c/em\u003e clumps contacted by the cutter head within a .25 m\u003csup\u003e2\u003c/sup\u003e is a measure of intensity of cutting within its swath. \u0026nbsp;The cutter head contacted all the clumps within .25 m\u003csup\u003e-2\u003c/sup\u003e quadrats 3/22 samples distributed evenly over 84 m (Fig 6). \u0026nbsp;The average intensity of cutting was .49 \u0026plusmn;.21 clumps .25m\u003csup\u003e-2\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClump cutting height\u003c/p\u003e\n\u003cp\u003eThe height \u003cem\u003eA. nodosum\u003c/em\u003e clumps are cut above the substrate reflects the degree of selectivity of the mechanical cutter head. Post harvest mechanical measurement of cut height in clumps from 2020 to 2022 commercial harvests from four areas averaged 64.4 to 93.4 cm range 37-212, N=1054.\u003c/p\u003e\n\u003cp\u003eThe proportion of cut and uncut clump total length in the swath reflected the selectivity of the machine\u0026rsquo;s cutter head (Fig 7). Clumps with evidence of recent cutting the mode was 50-75 cm versus 25- 50 cm length of uncut clumps (Fig 7).\u003c/p\u003e\n\u003cp\u003eShoots\u003c/p\u003e\n\u003cp\u003eContact of the cutter head with an \u003cem\u003eA nodosum\u003c/em\u003e clump does not sever all shoots in a clump. The incidence of cut shoots within clumps with evidence of harvest averaged .25 \u0026plusmn; .14 Range .05 to .68, (N= 1502) shoots (Fig 8).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe ability to define the targeted harvest areas (polygons) enhances area-based management providing a plot of annual harvest at a sub sector level.\u003c/p\u003e\u003cp\u003eThe relationship between exploitation rate and the area of a polygon is to a degree a reflection of the limitations of the chart plotter. The description of a swath is a simplification of the movement of the harvester within a bed. The chart plotter is tracking the vessels movements every 30 seconds at a resolution of 3\u0026ndash;5 m. When the operator moves the vessel laterally less than 5 m and within 30 sec the chart plotter does not record the distance. This limit of track resolution impacts the calculation of exploitation rate as the targeted area is less than 100 m\u003csup\u003e2\u003c/sup\u003e. Consequently, the calculated exploitation rates are generally overstated at this scale. Despite this limitation exploitation rates within the bed, one geographical scale above the polygon resulted in a maximum exploitation rate of 22%. The average commercial exploitation rate of summed polygons in 7 sectors harvesting 636 t in 2022 was 36.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9% (Sharp and Sharp \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe pattern of harvest within beds does not result in a clear cut of biomass or a homogenous exploitation rate within targeted portions of the beds. The operator selects portion of the beds optimal for economic return. The characteristics of the machine\u0026rsquo;s cutter head selects for the distal portions of individual clumps.\u003c/p\u003e\u003cp\u003eThe calculation of exploitation rates in this study was based on constants derived from averages of harvestable standing crop. Variation of biomass and distribution is related to both the harvest per unit effort and the harvesting strategies of the machine operator. The operator is paid a tonnage incentive and will choose to target the portion of the floating canopy providing a minimum kg h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and kg tide\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Operational limitations of the vessel result in the selection of beds within a sector by the operator to obtain an optimal harvest rate. Wind velocity, wave height tide level, distance from landing sites will impact on the location and degree of exploitation.\u003c/p\u003e\u003cp\u003eThe cutter head design and mode of cutting and gathering results in the characteristics of the post-harvest \u003cem\u003eA nodosum\u003c/em\u003e population and the habitat structure. The cutter head does not cut all the shoots of a clump at one height related to the surrounding collar; a combination of suction and forward movement of the cutter head and the depth of the water feed the floating distal portions of shoots within the clump into the cutter head at various heights. The cutter tends to cut horizontally the shoots suctioned into the cutter head. Despite the high proportion of the polygon swept by the cutter head not all clumps are contacted by the cutter head. The high density of shoots in clumps with lateral and primary apices un-truncated allow recovery of biomass.\u003c/p\u003e\u003cp\u003eThe cutting height is affected by the length distribution of the population as well as the relief of the substrate and the selectivity of the cutter head and machine operator. Boulder substrate prevents the cutter head from reaching the bottom compared to a less complicated bedrock or small rock shoreline.\u003c/p\u003e\u003cp\u003eThe cutter head operated under these limitations was extremely selective for length of clumps and within clumps for length of shoots. There was no clear cut above the scale of .25m\u003csup\u003e2\u003c/sup\u003e in a polygon or bed nor do all clumps within .25m\u003csup\u003e2\u003c/sup\u003e have all shoots cut. The incidence of cut shoots within clumps is the final scale of exploitation. Most shoots are left untruncated and their growing tips continue to contribute to the productivity of the bed. The selectivity for longer clumps and shoots combined with the vertical distribution of biomass in clumps allows the removal of biomass with a low impact on the clump\u0026rsquo;s ability to recover from the harvest.\u003c/p\u003e\u003cp\u003eThe degree of habitat impacts at sub sector scale is very dependent on the intensity of harvesting within the bed and ultimately on the changes in assemblages of \u003cem\u003eA nodosum\u003c/em\u003e clumps and shoots within a clump. \u003cem\u003eAscophyllum nodosum\u003c/em\u003e populations in southwestern Nova Scotia have sustained annual harvests for the past 64 years exceeding 20000 t yr-1 in 28 of the last 34 years. Harvest technology has changed several times between manual and mechanical techniques (Chopin and Ugarte \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Area based management has brought control of exploitation within sectors. Economic and logistical limits are factors selecting sectors for harvest and the portion of the beds targeted for harvest. Long term monitoring of population structure and biomass in targeted parts of the \u003cem\u003eA nodosum\u003c/em\u003e resource during decades of commercial exploitation have not found significant changes (Lauzon-Guay et al \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e, Lauzon-Guay et al \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e, Lauzon-Guay et al \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eAn issue of concern due to habitat impacts at landscape scale is fragmentation of the habitat and its impact on biodiversity (Yeager et al \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A patchy harvest can divide \u003cem\u003eA nodosum\u003c/em\u003e beds into smaller units for the short and medium term as the population recovers from cutting a portion of the canopy. A further analysis of the spatial distribution of tracks within beds can potentially provide a measure of degree and extent fragmentation and patchiness caused by harvests.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was fully funded by Scotia Garden Seafood 112 Water Street Yarmouth NS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corresponding author G Sharp is the sole proprietor of KCME Inc a consulting company. His company provides third party resource management and development research advisory services to seaweed buying and processing companies. Past clients have included Acadian SeaPlants Ltd, Nunavik Biosciences, Thorverk Iceland and Tidal Organics Inc.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe co-author Joshua Sharp is a full-time employee of Tidal Organics Ltd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data has been collected by accepted field methodology and is available in excel. Analysis was completed with open QGIS and MaxStat software.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corresponding author G Sharp and co-author J Sharp jointly contributed to study conception and design. Material and data collection was performed by J Sharp, data analysis was completed by G Sharp. Figure 1 3 4 were created by G Sharp, Figure 2 by J Sharp\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAng PO, Sharp GJ, Semple RE (1993) Changes in the population structure of Ascophyllum nodosum (L.) Le Jolis due to mechanical harvesting Hydrobiologica 261:321-326.\u003c/li\u003e\n\u003cli\u003eChopin T, Ugarte R (2006) The seaweed resource of eastern Canada in Critchley AT, Ohno M, Largo DB (eds) World Seaweed Resources: 46 p. DVD -ROM. ETI BioInformatics Amsterdam ISBN: 90 75000 80 4. \u003c/li\u003e\n\u003cli\u003eCousens R (1984) Estimation of annual production by the intertidal brown alga \u003cem\u003eAscophyllum nodosum\u003c/em\u003e (L.) Le Jolis Bot Mar 27:217-227\u003c/li\u003e\n\u003cli\u003eLauzon-Guay JS, Ugarte RA, Morse BL, Robertson CA Jour Appl Phyco 2021a 33:1695\u0026ndash;1708\u003c/li\u003e\n\u003cli\u003eLauzon-Guay, JS., Ugarte,R, Morse, BL \u0026amp; Robertson C 2021b. Biomass and height of \u003cem\u003eAscophyllum nodosum\u003c/em\u003e after two decades of continuous commercial harvesting in eastern Canada. J Appl Phyco https://doi.org/10.1007/s10811-021-02427-x.\u003c/li\u003e\n\u003cli\u003eLauzon‑Guay JS, Feibel A, Morse BL, Ugarte RA (2023) Morphology of \u003cem\u003eAscophyllum nodosum\u003c/em\u003e in relation to commercial harvesting in New Brunswick, Canada J App Phyco 35:2371\u0026ndash;2381\u003c/li\u003e\n\u003cli\u003eLazo L, Chapman ARO (1993) Components of crowding in a modular seaweed: sorting through the contradictions Mar Ecol Prog Ser 174:257-267.\u003c/li\u003e\n\u003cli\u003eNSDFA (1997) Rock Weed Regulations (RWR) S.N.S. Part VI (Sea Plants Harvesting) of the Fisheries and Coastal Resources Act. Chapter 25, Acts of 1996 and (to date) the Sea Plants Harvesting Regulations of the Fisheries and Coastal Resources Act, 1989, Chapter 416.\u003c/li\u003e\n\u003cli\u003eRangely R, Davis J (2000) Management of low trophic level fisheries in the face of uncertainty Marine Huntsman Marine Science Centre Occasional Report 00/1 p 94.\u003c/li\u003e\n\u003cli\u003eSharp GJ (1986) \u003cem\u003eAscophyllum nodosum\u003c/em\u003e and its harvesting in eastern Canada, in Case Studies of Seven Commercial Seaweed Resources, FAO Fisheries Technical Paper 281. Rome, Italy: Food and Agriculture Organization of the United Nations pp 3-48.\u003c/li\u003e\n\u003cli\u003eSharp GJ, Trembay D (1989). An assessment of \u003cem\u003eAscophyllum nodosum\u003c/em\u003e resources in Scotia Fundy CAFSAC Res. Doc. 89/1 p 19.\u003c/li\u003e\n\u003cli\u003eSharp GJ, Ang P, MacKinnon D (1994) Rockweed (\u003cem\u003eAscophyllum nodosum\u003c/em\u003e) (L.) Le Jolis harvesting in Nova Scotia: its socioeconomic and biological implications for coastal zone management. Proc Coastal Zone Canada 94: 1632-1644.\u003c/li\u003e\n\u003cli\u003eSharp GJ, Sharp JT (2024) Estimating \u003cem\u003eAscophyllum nodosum\u003c/em\u003e (L.) Le Jolis harvesting impacts using GPS Tracking of mechanical harvesters in Nova Scotia, Canada. J Appl Phycol 36: 605\u0026ndash;610. \u003c/li\u003e\n\u003cli\u003eUgarte, R, Sharp G (2001) A new approach to seaweed management in eastern Canada: the case of \u003cem\u003eAscophyllum nodosum\u003c/em\u003e Cah. Biol. Mar. 42:63-70. \u003c/li\u003e\n\u003cli\u003eUgarte R, Sharp GJ, Moore B, (2006) Changes in the brown seaweed \u003cem\u003eAscophyllum nodosum\u003c/em\u003e (L.) Le Jol. plant morphology and biomass produced by cutter rake harvests in southern New Brunswick, Canada J Appl Phycol 18:351-359\u003c/li\u003e\n\u003cli\u003eUgarte, R., Sharp, G. (2012) Management and Production of the brown algae \u003cem\u003eAscophyllum nodosum\u003c/em\u003e in the Canadian Maritimes J. Appl. Phycol 24: 409- 416. \u003c/li\u003e\n\u003cli\u003eSchmidt AL, Coll M, Romanuk T, Lotze HK (2015) Ecosystem structure and services in eelgrass Zostera marina and rockweed \u003cem\u003eAscophyllum nodosum\u003c/em\u003e habitats Mar Ecol Prog Ser 437: 51\u0026ndash;68.\u003c/li\u003e\n\u003cli\u003eYeager LA, Estrada J, Holt K, Keyser S, Olke TA (2020) Are Habitat Fragmentation Effects Stronger in Marine Systems? A Review and Meta-analysis Current Landscape Ecology Reports (2020) 5:58-67\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ascophyllum, Landscape, GPS, Management, Area Based, Exploitation","lastPublishedDoi":"10.21203/rs.3.rs-7745870/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7745870/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe harvesting of \u003cem\u003eAscophyllum nodosum (L.) Le Jolis \u003c/em\u003eresources of Nova Scotia and New Brunswick Canada are regulated by area-based management since 1989. The Tidal Organics Inc harvesting company has five leases with responsibility to manage large 928.5 h to 76677.7 h of the coastline. A mechanical harvester was introduced to Nova Scotia by Tidal Organics with (Global Positioning System) GPS charts of daily harvesting to 3-5 m.\u0026nbsp; Tracking and landing data provides a comprehensive landscape view of resource utilization. GPS technology with traditional biomass sampling biomass and remote sensing of bed areas defined exploitation rates from the scale of bays to sectors .9 -17.6 ha, to beds 2.33± .47 ha to targeted polygons ha, .09 ± .01ha and swath of the cutter head 02± .15 N=30. Optimally harvestable biomass in Lunenburg Bay was 59% of the total and 4.6% was un-harvestable. The beds targeted by the mechanical harvester were exploited at 8.77 ± 9.06 % N=30 of harvestable biomass. The mechanical harvester was selective at the scale of .25m\u003csup\u003e2\u003c/sup\u003e within the swath of the cutter head for A nodosum clumps, clump length, and shoots within clumps.\u003c/p\u003e","manuscriptTitle":"A landscape view of Ascophyllum nodosum (L.) Le Jolis management and harvesting impacts in Southwestern Nova Scotia Canada","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-16 08:13:29","doi":"10.21203/rs.3.rs-7745870/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9d1e52b0-a2e4-402a-b12a-81a95babac49","owner":[],"postedDate":"October 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-03T17:23:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-16 08:13:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7745870","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7745870","identity":"rs-7745870","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}