•We introduce an innovative habitat selection framework for marine tracking data.•Coastal fringing vegetation drives space use in a juvenile elasmobranch.•Juvenile sharks avoid once-pristine areas, ...now human coastal development sites.•Establish shark behaviour as indicator of habitat quality and area for protection.•Findings have regional and global implications for the management of coastlines for sharks.
Nearshore environments represent important habitat for many marine vertebrates during their early-life stages. Globally, these coastal sites are impacted by human activities that have the potential to negatively impact biodiversity in ways we do not yet fully appreciate. To improve our understanding of the relevance of mangrove removal in tropical elasmobranch nursery grounds, we studied the globally Vulnerable lemon shark (Negaprion brevirostris) in a mangrove-fringed lagoon in Bimini, The Bahamas, following a decade of coastal development and habitat disruption. We used two years of acoustic telemetry detections and generalised linear mixed models (GLMMs) to evaluate the link between juvenile shark spatial behaviour and six features of their physical environment. AIC-adjusted model-averaged predictions of habitat selection demonstrated that distance from the central mangrove forest was the most important feature for sharks. After updating model averaging to account for overall preference for proximity to the central forest, we found that medium density seagrass was secondarily preferred over all other habitat types (bare sand, sargassum, urban and rocky outcrops, and deep water) within the core use area (probability of use ≥ 50 %). Locally, our results support including this core area in future marine protected area considerations. More broadly, in the face of rapid global population declines of many elasmobranchs and wide-spread habitat fragmentation in coastal marine nurseries, we identified widely applicable habitat features underpinning an area of high ecological significance for a threatened shark during a vulnerable life stage and outlined a habitat selection framework suitable for using marine vertebrate movement data as ecological indicators for future applied conservation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Understanding the supply and demand characteristics of ecosystem services (ESs) and their trade-offs is the basis for effective ecosystem management and the improvement of human well-being. However, ...current management practices based on the trade-offs between the supply and demand for ESs remain limited. This study aimed to integrate ES trade-offs into regional spatial management. With Changzhi, China, as the study area, this study evaluated the supply, demand, and trade-offs of food provision, water conservation, soil retention, and carbon sequestration by linking multi-source data and using spatial analysis tools, including the InVEST model, ArcGIS, and GeoDA. Based on the trade-offs and importance of different ecological functions, we constructed an urban spatial management framework and proposed recommendations for optimization in different management zones. The results showed that (1) the supply and demand for multiple ESs exhibited spatial heterogeneity. Except for water conservation, the supply of other ESs met the demand of the city, but there were still obvious deficits in some regions. (2) In terms of the ES supply, there were trade-offs between food production and other ESs, and synergies existed among water conservation, soil retention, and carbon sequestration. In terms of the ES demand, the four ESs exhibited synergistic relationships. In the cluster analysis, ES supply and demand were divided into four ES bundles, respectively. (3) The spatial mismatch of ESs in the sub-watersheds of the study area was obvious. The ESDR coldspots for the four ESs were primarily located in the urban built-up areas in the central and southern regions of the city. The ESDR hotspots of soil retention and carbon sequestration were mainly distributed in the eastern and northwestern regions of Changzhi, which are less urbanized. There were few ESDR hotspots for food production and water conservation. (4) Based on the regional spatial management framework, Changzhi was divided into ten zones, including extremely important, moderately important, important, supply–demand risk management, soil erosion management, and high food production areas. The results and conclusions of this study provide a basis for spatial planning and ecosystem management.
•The trade-offs of ecosystem services were evaluated from three dimensions: supply-supply, demand-demand, and supply-demand.•The spatial management framework was constructed based on the trade-offs and ecological functional importance.•Spatial management zoning with corresponding recommendations were proposed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Information on the movements and population structure of an exploited fish species is vital for determining the appropriate spatial scale at which management should occur to ensure sustainable ...harvesting. However, such information exists for very few exploited species. Large-scale patterns and drivers of movement were examined for an iconic recreational sciaenid species, mulloway (Argyrosomus japonicus), in coastal eastern Australia using an angler-assisted tag-recapture dataset. Over 4300 individuals were tagged and released across 1005 km of coastline over three decades (1988–2017). Six-hundred and fifty-seven individuals were subsequently recaptured at a rate of 15.1% over the same time period. Average time at liberty was 216 (±9) days (range: 0–1954 days), with distances moved ranging from 0 to 355 km. Median movement distance was 4 km, and a large proportion of individuals (73%) were recaptured within 10 km of release locations. Thirty one percent of individuals were recaptured at release locations (< 1 km) and 81% in the same estuary. However, 7% moved distances of > 100 km. Generalised additive modelling revealed that release latitude, body size and time at liberty were significant predictors of distance moved. Greater distances moved were observed for fish tagged at lower latitudes, at larger sizes and over longer periods at liberty. Results indicate that A. japonicus are primarily restricted to small movements (< 10 km) in eastern Australia and display strong site fidelity, despite being capable of movements over larger scales (100s of km). This spatial scale of movement is also much smaller than the current ‘jurisdictional’ scale of management in this region (~1000 km). Assessment and management of A. japonicus in eastern Australia may therefore need to be re-examined considering these findings and potentially undertaken at more localised spatial scales in the future. This study also highlights the importance of citizen science in the cost-effective generation of a sufficiently broad spatio-temporal dataset required to detect the movement patterns revealed here.
•Released over 1000 km and three decades, tagged Argyrosomus japonicus were recaptured at a rate of 15.1%.•Movements occurred predominantly over small spatial scales (< 10 km) in eastern Australia.•Fish tagged at lower latitudes, at larger sizes and over longer periods at liberty moved greater distances.•Current spatial management of the stock may consequently need to be re-examined.•Citizen science was key in the cost-effective generation of the large-scale tagging dataset used.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•Management of Adriatic Sea resources largely disregards meaningful spatial issues.•A method to estimate spatial LPUE and landings is proposed.•Vessel-specific monthly landings are estimated by ...origin and destination.•The dynamics of the Adriatic bottom trawling fleet is described in detail.•Strengths and shortcomings of the status-quo management paradigms are discussed.
At present, the assessment and management of Adriatic Sea fishery resources are based on data that do not fully account for the complex spatial patterns arising from fleet behavior and/or species’ behavior and biology, mainly because logbooks do not guarantee adequate coverage of the fishing activity exerted by the fleet. For data collection, the Adriatic Sea is divided into two management areas (namely FAO Geographical Sub-Areas–GSAs). To account for these spatial patterns while using the data available, we propose a method for estimating the monthly landings of Italian trawlers operating in the Adriatic Sea at a higher spatial resolution than the GSA. We use a stepwise approach based on the combined analysis of questionnaire-derived vessel-specific landings and the spatial activity of the vessels with respect to a set of fishing grounds. Thus, we sequentially 1) analyze the available vessel monitoring system data, 2) partition the study area into fishing grounds (the origin of the landings), 3) cross analyze vessel-specific fishing efforts with the available vessel-specific monthly landings to estimate the LPUE of each fishing ground, and 4) estimate the monthly landings (by vessel, fishing ground, and harbor) for the whole fleet and the monthly fluxes between fishing grounds (origin) and landing harbors (the destination of the landings). We apply the method to two species: the Norway lobster and the European hake. For both species, we find a few fishing grounds to be consistently more productive than others and the landings per harbor to vary greatly but with few harbors regularly receiving a significant share. In particular, the results suggest that the Pomo/Jabuka pit area represents a critical area for both species. Additional outcomes include a detailed characterization of the activity of the Adriatic bottom trawling fleet, highlighting the strengths and shortcomings of the official data available. We discuss the results in the context of the current management paradigm.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The expansion of the world's merchant fleet poses a great threat to the ocean's biodiversity. Collisions between ships and marine megafauna can have population-level consequences for vulnerable ...species. The Endangered whale shark (Rhincodon typus) shares a circumglobal distribution with this expanding fleet and tracking of movement pathways has shown that large vessel collisions pose a major threat to the species. However, it is not yet known whether they are also at risk within aggregation sites, where up to 400 individuals can gather to feed on seasonal bursts of planktonic productivity. These “constellation” sites are of significant ecological, socio-economic and cultural value. Here, through expert elicitation, we gathered information from most known constellation sites for this species across the world (>50 constellations and >13,000 individual whale sharks). We defined the spatial boundaries of these sites and their overlap with shipping traffic. Sites were then ranked based on relative levels of potential collision danger posed to whale sharks in the area. Our results showed that researchers and resource managers may underestimate the threat posed by large ship collisions due to a lack of direct evidence, such as injuries or witness accounts, which are available for other, sub-lethal threat categories. We found that constellations in the Arabian Sea and adjacent waters, the Gulf of Mexico, the Gulf of California, and Southeast and East Asia, had the greatest level of collision threat. We also identified 39 sites where peaks in shipping activity coincided with peak seasonal occurrences of whale sharks, sometimes across several months. Simulated collision mitigation options estimated potentially minimal impact to industry, as most whale shark core habitat areas were small. Given the threat posed by vessel collisions, a coordinated, multi-national approach to mitigation is needed within priority whale shark habitats to ensure collision protection for the species.
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•The marine biosphere is at risk from expanding maritime human activities.•Collisions between large ships and marine megafauna are in need of management attention.•Shipping was measured in over 50 global whale shark aggregation sites.•Peaks in shipping activity often coincided with peak seasonal occurrences of whale sharks.•Changes to ship speed or transiting routes can be targeted in small, localised zones.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Development of guidance for environmental management of the deep-sea mining industry is important as contractors plan to move from exploration to exploitation activities. Two priorities for ...environmental management are monitoring and mitigating the impacts and effects of activities. International regulation of deep-sea mining activities stipulates the creation of two types of zones for local monitoring within a claim, impact reference zones (IRZ) and preservation reference zones (PRZ). The approach used for allocating and assessing these zones will affect what impacts can be measured, and hence taken into account and managed. This paper recommends key considerations for establishing these reference zones for polymetallic nodule mining. We recommend that zones should be suitably large (Recommendation 1) and have sufficient separation (R2) to allow for repeat monitoring of representative impacted and control sites. Zones should be objectively defined following best-practice and statistically robust approaches (R3). This will include the designation of multiple PRZ and IRZ (R4) for each claim. PRZs should be representative of the mined area, and thus should contain high -quality resource (R5) but PRZs in other habitats could also be valuable (R6). Sediment plumes will influence design of PRZ and may need additional IRZ to monitor their effects (R7), which may extend beyond the boundaries of a claim (R8). The impacts of other expected changes should be taken into account (R9). Sharing PRZ design, placement, and monitoring could be considered amongst adjacent claims (R10). Monitoring should be independently verified to enhance public trust and stakeholder support (R11).
•Two types of environmental monitoring zones are required per deep-sea mining claim.•11 recommendations are presented for establishing these reference zones.•Effective monitoring programmes require robust statistical design of zones.•To determine statistical power, comprehensive baseline surveys are required.•Zones should be sufficient to allow assessment of a range of impacts in all affected habitats.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Subseasonal forecasts could provide insight into future risk to marine ecosystems.•Reducing fisheries bycatch in a changing ocean is a unique management challenge.•We integrate a species ...co-occurrence model with subseasonal oceanographic forecasts.•Spatiotemporal variability in bycatch risk is detectable at the weekly stage.•Study represents first step in the development of an ongoing bycatch avoidance tool.
Over the past decade, substantial progress has been made in projecting and predicting the spatial distribution of many marine species at seasonal to multidecadal time scales. However, managers and fishers often need to make decisions at much shorter time scales. Subseasonal environmental forecasts, which generate predictions over one to several weeks, can now be combined with species-specific habitat preference data to create ecological forecasts that could facilitate dynamic spatial management. The development of such predictive tools could aid in identifying optimal times and areas for fishers to maximize target catch and avoid nontarget catch. Nontarget catch, or bycatch, can have numerous and potentially severe economic and ecological consequences. Here, we focus on a population of anadromous fish known collectively as river herring (alewife and blueback herring), as they are species of concern and are heavily impacted by bycatch. Using bottom trawl survey data from the Northeast US and subseasonal forecasts of sea surface temperature, we constructed a bycatch risk model to generate probabilistic predictions of river herring distributions in regions frequented by the US mid-water trawl fishery. Assessments of model skill showed that our ecological model performed well in predicting the distribution of river herring and that subseasonal forecasts were effective at 1-week timeframes. There was a clear seasonal effect on forecasted bycatch risk throughout the Northeast US, with particularly high risk in winter and spring months. Importantly, variability in risk was detectable at the weekly timescale and our model identified specific areas and times that fishers should avoid in order to decrease their likelihood of bycatch. The bycatch risk forecast developed in this study is a significant advance from near-real time forecasts and the foundation to build forecast systems by combining species co-occurrence models with subseasonal forecasts. As these subseasonal forecasts are available globally, this approach could be adapted to facilitate the management of other natural resource conflicts around the world.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Spatial management measures are currently being used to manage bycatch and discards, given the spatial heterogeneity of fish distributions. However, permanent fishing closures are often poorly ...implemented, unresponsive to stock dynamics and do not achieve their management objectives. Recently, real‐time spatial management tools for managing bycatch and discards implemented under either a comanagement or self‐governance approach have been introduced in Europe and the US. Real‐time catch and discard information is shared among fishers to incentivise and encourage vessels to leave areas of high bycatch. Here, the similarities and differences, in governance, implementation and management of ten real‐time spatial management systems from across Europe and the US are reviewed. A framework is developed to characterize the attributes associated with voluntary, private and regulatory real‐time spatial management tools. Challenges and management practices in the different case studies are reviewed providing insights for designing these spatial management tools. The results illustrate that real‐time spatial management approaches can create incentives for fishers to develop, use and share information and technology to avoid undesired catch. Compared with Europe, the US has developed spatial management tools with more truly real‐time mechanisms and with greater involvement of the fishing industry in designing and operating the tools.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
•We developed a high-resolution spatiotemporal state-space model for the snow crab (Chionoecetes opilio) population in the Eastern Bering Sea (EBS).•The model was used to refine the representation of ...spatial processes in integrated population models, facilitate understanding of the drivers of spatiotemporal population dynamics, and provide new insights for management advice.•The model implicitly accounts for seasonal movement between the time of the survey and that of fishery to estimate fine-scale spatial population dynamic and fishing impacts, including potential environmental drivers.•We quantify spatiotemporal variation in exploitable abundance, fishing mortality, recruitment, and mature and immature abundance.•The model estimated declines in exploitable abundance and in fishing mortality with variable spatial distributions, and sporadic recruitment, spatially concentrated in the northeast EBS.
Considering spatial processes in population dynamics models can be difficult because of data limitations and computational costs. We adapted a high-resolution spatiotemporal assessment framework to better address fine-scale spatial heterogeneities based on theories of fish population dynamics and spatiotemporal statistics. Specifically, we developed a size-based state-space model for the snow crab (Chionoecetes opilio) population in the Eastern Bering Sea (EBS) to refine the representation of spatial processes in integrated population models, facilitate understanding of the drivers of spatiotemporal population dynamics, and provide new insights for management advice. The model fits to spatial survey and fishery-dependent catch data. It implicitly accounts for seasonal movement between the time of the survey and that of fishery to estimate fine-scale spatial population dynamic and fishing impacts, including potential environmental drivers. We quantify, for the first time, spatiotemporal variation in exploitable abundance, fishing mortality, recruitment, and mature and immature abundance. The model estimated declines in exploitable abundance and in fishing mortality with variable spatial distributions, and sporadic recruitment, spatially concentrated in the northeast EBS. Few spatial assessments have been used as the basis for management advice and we consider this study as a step towards the integration of spatial dynamics in stock assessment.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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