The relationship between metapopulation stability and connectivity has long been investigated in ecology, however, most of these studies are focused on theoretical species and habitat networks, having limited ability to capture the complexity of real-world metapopulations. Network analysis became more important in modeling connectivity, but it is still uncertain which network metrics are reliable predictors of persistence. Here we quantify the impact of connectivity and larval life history on marine metapopulation persistence across the complex seascape of southeast Australia. Our work coupled network-based approaches and eigenanalysis to efficiently estimate metapopulation-wide persistence and the subpopulation contributions. Larval dispersal models were used to quantify species-specific metapopulation connectivity for five important fisheries species, each summarized as a migration matrix. Eigenanalysis helped to reveal metapopulation persistence and determine the importance of nodelevel network properties. Across metapopulations, the number of local outgoing connections was found to have the largest impact on metapopulation persistence, implying these hub subpopulations may be the most influential in real-world metapopulations. Results also suggest the length of the pre-competency period may be the most influential parameter on metapopulation persistence. Finally, we identified two major hot spots of local connectivity in southeast Australia, each contributing strongly to multispecies persistence. Managers and ecologists would benefit by employing similar approaches in making more efficient and more ecologically informed decisions and focusing more on local connectivity patterns and larval competency characteristics to better understand and protect real-world metapopulation persistence. Practically this could mean developing more marine protected areas at shorter distances and supporting collaborative research into the early life histories of the species of interest.
Spatial considerations are important at multiple stages in the development of a deep-sea mining (DSM) project, from resource definition, to identification of preservation and management zones within a contract area, to planning of suitable ecological strata for baseline studies and impact assessment, to mine planning and adaptive management. Large investments are made to collect remote sensing data early in exploration to support geological resource studies, but environmental considerations are often instigated at later stages of exploration and can become disconnected from spatial frameworks. We outline a process of harmonizing the environmental and geological aspects of DSM project development by incorporating a habitat approach early in the development cycle. This habitat approach supports ecosystem-based management, which is a central requirement of environmental assessments. Geostatistical techniques are described that are used alongside a hierarchical classification scheme to describe and map geoforms and substrates. This foundational habitat model can form the basis of spatially explicit ecosystem models and can inform sampling design and spatial planning at critical junctures of a project development, ensuring that sampling campaigns are connected by an ecosystem logic early in the cycle. We provide an example application from the NORI-D polymetallic nodule exploration contract area in the Clarion-Clipperton Zone.
Species distribution models (SDMs) are commonly used in ecology to predict species occurrence probability and how species are geographically distributed. Here, we propose innovative predictive factors to efficiently integrate information on connectivity into SDMs, a key element of population dynamics strongly influencing how species are distributed across seascapes. We also quantify the influence of species-specific connectivity estimates (i.e., larval dispersal vs. adult movement) on the marine-based SDMs outcomes. For illustration, seascape connectivity was modeled for two common, yet contrasting, marine species occurring in southeast Australian waters, the purple sea urchin, Heliocidaris erythrogramma, and the Australasian snapper, Chrysophrys auratus. Our models illustrate how different species-specific larval dispersal and adult movement can be efficiently accommodated. We used network-based centrality metrics to compute patch-level importance values and include these metrics in the group of predictors of correlative SDMs. We employed boosted regression trees (BRT) to fit our models, calculating the predictive performance, comparing spatial predictions and evaluating the relative influence of connectivity-based metrics among other predictors. Network-based metrics provide a flexible tool to quantify seascape connectivity that can be efficiently incorporated into SDMs. Connectivity across larval and adult stages was found to contribute to SDMs predictions and model performance was not negatively influenced from including these connectivity measures. Degree centrality, quantifying incoming and outgoing connections with habitat patches, was the most influential centrality metric. Pairwise interactions between predictors revealed that the species were predominantly found around hubs of connectivity and in warm, high-oxygenated, shallow waters. Additional research is needed to quantify the complex role that habitat network structure and temporal dynamics may have on SDM spatial predictions and explanatory power.
The Cook Islands (CI) possesses within its Exclusive Economic Zone (EEZ) a massive field of polymetallic nodules representing one of the world's largest undeveloped cobalt deposits, along with large quantities of other metals critical to achieving global energy transition targets. In February of 2022 the Seabed Minerals Authority (SBMA) of the CI granted licenses to three companies to conduct nodule exploration programs. This paper describes the process adopted by Moana Minerals, one of the license holders, to define new ways of conducting exploration which are focused on addressing the greatest challenge to Deep Sea Mining (DSM) development – that of securing the social license to advance to eventual mining of the resources. While it is generally true for any DSM project, obtaining license to operate within the EEZ of a sovereign nation requires even more focus on socio-economic and cultural concerns. Hence Moana Minerals invested even before exploration license award in the completion of an Environmental and Social Impact Assessment (ESIA) scoping study. This exercise helped to define the key questions and concerns, the range of stakeholders in the ESIA process, and began to construct the Ecosystem Based Model which is the heart of our ESIA program. We describe our employment of the increasingly adopted best practice of Ecosystem Based Management (EBM), which considers the entire ecosystem and its services, and the complex associated interactions for a "whole of system" approach. We discuss how this model is used to help communicate relationships between potential stressors associated with seabed mining and ecosystem responses, as well as how it is used to identify thresholds and guide development and adaptation of ecosystem management approaches. Given the challenges of the remoteness of the Cook Islands, limited exploration assets in the region, and ongoing supply chain delays and limitations, our early analysis of how best to execute an EBM-based program concluded that a dedicated research vessel properly outfitted with a full suite of scientific gear would be key to success. We describe our program to economically develop such an exploration system through repurposing an offshore support vessel, with an aim towards maximum suitability for Cook Islands-based exploration and other deep sea exploration work in the region as well as other potential high value regional applications. Finally, we discuss operations to date using this critical exploration-enabling asset.
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