This study investigates the influence of model resolution on the representation of Antarctic Intermediate Water (AAIW) hydrographic properties and the role of eddies in the meridional transport of salt using three simulations from the HadGEM3-GC3.1 HighResMIP family with varying ocean resolutions: the 1 degrees LL model (parameterized eddies), the 1/4 degrees MM model (eddy-present), and the 1/12 degrees HH model (eddy-rich). The control-1950 simulation is compared with the WOA18 climatology. Results show that increasing model resolution improves the representation of AAIW core properties (temperature, salinity, and density) and its northward extent. The LL model shows a restricted low-salinity tongue compared to observations, whereas the MM and HH models are more aligned with observations. Regions of high eddy kinetic energy coincide with major AAIW pathways in the MM and HH models, while the LL model is not able to capture the fine scale of the western boundary currents. The meridional salt transport is decomposed into its mean and eddy component and a compensation of both terms is found in MM and HH. The intermediate layer contributes to close to 30% of the total northward salt transport. Although total and eddy meridional salt transports are similar between MM and HH for the intermediate layer, the HH model contains more coherent eddies with greater westward propagation, suggesting distinct underlying mechanisms of salt transport. The findings highlight the limitations of the LL model in reproducing AAIW properties and circulation, with major improvements in the MM and HH models.

Anthropogenic metal cycles shape resource availability, recycling performance and long-term sustainability: understanding their dynamic behaviour, including long-term stability and sensitivity to change, is essential for sustainable resource management and supply-chain resilience. Here, a system of ordinary differential equations for the global copper cycle linking extraction, processing, manufacturing, use, waste management and recycling is developed to analyse the dynamic equilibrium, stability and sensitivity of metal cycles. Results demonstrate that dissipative losses are necessary for asymptotic stability of the stocks, underscoring the importance of quantifying dissipation and recycling for long-term forecasting. Multi-decadal copper inventory oscillations can be simulated by integrating a second-order investment accelerator to endogenise mining dynamics, while also creating conditions for endogenous growth. Sensitivity analysis shows that new and old scrap rates exert the largest influence on the system's dynamics, whereas refining and manufacturing flows provide the strongest stabilising effect. This study extends material flow analysis with tools from dynamical systems theory by linking physical flows with economic feedbacks and offers a general framework for assessing stability, resilience and policy levers in metal cycles and other resource systems.

Natural resource cycles operate under both physical constraints and socio-economic drivers. To represent these coupled dynamics, a mineral commodity model is developed by integrating material flow analysis with market behaviour using a system of ordinary and delay differential equations 1 . The formulation is grounded in mass conservation and the cobweb economic theorem, enabling simulation of anthropogenic metal stocks, flows and market variables, including price dynamics. An application to the global copper cycle demonstrates the model's ability to reproduce long-term trends in both material flows and market determinants. Numerical integration of the differential equations shows that longer mining lead times amplify and extend price fluctuations, whereas shorter delays lead to more stable cycles. Stability and eigenvalue sensitivity analyses 2 reveal that new and old scrap flows dominate overall dynamics, while refining and manufacturing activity provides the strongest stabilising influence. Dissipative flows and alternative recycling (tailings, slag and landfills) affect the system's speed of convergence towards equilibrium. This work illustrates the feasibility of unifying physical and economic theories in the simulation of resource systems. The framework also accommodates other economic mechanisms, such as the second-order accelerator of investment 3 , offering further avenues for advancing resource cycle modelling. Introducing this economic formalism to the equation set generates endogenous oscillations consistent with observed multi-decadal fluctuations in copper inventories 4 , thereby proposing a mechanistic explanation for cyclical behaviour in metal supply. The results highlight the importance of integrating theories from social sciences and economics into the modelling of resource cycles to improve forecasts of material flows and optimize exploitation and future use.

Small Island Developing States (SIDS) are a group of 58 nations identified by the United Nations as facing unique sustainability challenges, including high exposure to climate change, lack of data, and limited resources. The effects of climate change are already observed in SIDS, notably an increase in the magnitude and frequency of natural disasters, marine biodiversity loss, ocean acidification, coral bleaching, sea-level rise, and coastal erosion. The coastal zone is considered to be the main economic, environmental, and cultural resource of SIDS. Monitoring coastal changes is therefore essential to protect communities, biodiversity, natural landscapes, and their economies, as well as to help them adapt to and mitigate against climate change.This talk presents the use of remote sensing data to monitor and analyse the evolution of small islands. Open-access satellite missions, namely Landsat (NASA) and Sentinel (ESA), provide imagery with spatial resolutions of 10 to 60 metres and temporal resolutions of 5 to 16 days. These capabilities enable the retrieval of high-temporal-resolution time series of coastline positions across islands worldwide.A specific focus is placed on the Maldives (Indian Ocean) due to its low elevation and extensive human interventions. Existing literature lacks a comprehensive understanding of the patterns of coastal changes, as well as the main anthropogenic and environmental drivers involved, which operate across diverse temporal (e.g., daily, seasonal, multi-decadal) and spatial scales (e.g., site-specific or atoll-wide). Maldivian coastlines are not systematically or frequently monitored, such that sub and interannual variability and the geomorphological responses to climate forcings, such as the Indian Monsoon and the Indian Ocean Dipole, are not understood.To address this research gap, a data-driven framework was developed, leveraging remote sensing, in situ measurements, and open-access databases. This framework quantifies and disentangles coastal changes through three steps: firstly, an image segmentation algorithm that exploits characteristic spectral features was developed to extract the shape of small islands over time, providing reliable monthly time series of coastline positions. Secondly, time series decomposition was conducted, separating time series into trend, seasonality, and residuals. Each component was analysed separately using different methods: trend analysis to investigate the impacts of human activities (e.g., land reclamation, sand mining, shoreline armouring) and climate change (e.g., coral growth, sea-level rise) on natural coastal responses; seasonality analysis to explore sub- and inter-annual drivers, including the Indian Monsoon and the Indian Ocean Dipole; and residual analysis to quantify lagged effects of met-ocean conditions (e.g., waves, sea level) through causal inference methods. Thirdly, results are generated for several hundreds of islands, identifying regional patterns across atolls and illustrating how met-ocean conditions influence coastlines on a larger scale.Overall, this novel approach integrates advanced remote sensing and data science techniques, providing an unprecedented analysis of coastal dynamics at both fine and large scales, supporting better-informed environmental policies, urban planning, and marine infrastructure development to ensure sustainable management and resilience of these ecosystems.

This review explores the integration of Indigenous Knowledge and Skills (IKS) in mining operations, aimed at developing a comprehensive understanding of how these knowledge systems are embedded throughout the mining life cycle. The study systematically reviewed relevant literature from three electronic databases using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eighteen articles that met the inclusion criteria were included in the final analysis. Key findings reveal that qualitative methods, particularly interviews, are predominantly used to capture Indigenous perspectives. The research is regionally concentrated in Australia, with significant contributions from Canada, Papua New Guinea, and the USA. The studies encompass various Indigenous groups, highlighting varied cultural contexts and knowledge systems. Traditional ecological knowledge, a subset of IKS, is frequently integrated into mine planning and rehabilitation, demonstrating its practical value in sustainable mining practices. Factors facilitating the integration of IKS include supportive policies and laws, community leader involvement, and alignment with community expectations. Our findings contribute to the understanding of IKS in mining operations by providing a detailed overview of IKS integration in the mining life cycle, emphasising the importance of qualitative research, regional and cultural diversity, and their practical benefits.

Acid mine drainage (AMD) is an environmental concern that needs to be addressed by some mining industries because of its high concentrations of metals and acidity that destroy affected ecosystems. Its formation typically persists beyond the operating life of a mine site. Its management is even more challenging for sites that are abandoned without rehabilitation. In this study, a legacy copper–gold mine located in Sto. Niño, Tublay, Benguet, Philippines, generating a copper- and manganese-rich AMD (Cu, maximum 17.2 mg/L; Mn, maximum 2.90 mg/L) at pH 4.59 (minimum) was investigated. With its remote location inhabited by the indigenous people local community (IPLC), a novel limestone-based hybrid passive treatment system that combines a limestone leach bed (LLB) and a controlled modular packed bed reactor (CMPB) has been developed from the laboratory and successfully deployed in the field while investigating the effective hydraulic retention time (HRT), particle size, and redox conditions (oxic and anoxic) in removing Cu and Mn and increasing pH. Laboratory-scale and pilot-scale systems using simulated and actual AMD, respectively, revealed that a 15 h HRT and both oxic and anoxic conditions were effective in treating the AMD. Considering these results and unsteady conditions of the stream in the legacy mine, a hybrid multi-stage limestone leach bed and packed bed were deployed having variable particle size (5 mm to 100 mm) and HRT. Regular monitoring of the system showed the effective removal of Cu (88.5%) and Mn (66.83%) as well as the increase of pH (6.26), addressing the threat of AMD in the area. Improvement of the lifespan of the system needs to be addressed, as issues of Cu-armoring were observed, resulting in reduced performance over time. Nonetheless, the study presents a novel technique in implementing passive treatment systems beyond the typical treatment trains reported in the literature.

A legacy copper mine in Sto. Nino, Barangay Ambassador, Tublay, Benguet, Philippines, has generating acid mine drainage (AMD), posing environmental and social challenges affecting access to clean water for domestic use in mine-impacted areas. With multiple water sources in the area, classification and prioritization of use, as well as treatment intervention are necessary. This study presents and develops a novel water pollution index (WPI-AMD) designed to assess domestic water quality in AMD-impacted mining areas. The WPI-AMD utilizes a multi-criteria decision-making (MCDM) tool called the weighted aggregated sum product assessment (WASPAS) approach, integrating both additive and multiplicative functions to overcome shortcomings of existing water quality and pollution indices (WQPI). WPI-AMD includes careful selection, categorization, weighting, normalization, calibration, and aggregation of relevant geochemical parameters. Sampling was conducted in the legacy mine to determine the geochemistry of the identified water sources. The results show that WPI-AMD effectively evaluates AMD-impacted bodies for domestic use, providing more accurate assessment than other WQPI in terms of eclipsing percentage, agreement with expert judgement, and classification accuracy. Thus, WPI-AMD is a promising tool for water resource management in mining-affected areas, facilitating the classification of water bodies according to their suitability for domestic use and in identifying critically polluted water bodies that require intervention. The ability of WPI-AMD to integrate multiple geochemical parameters into a single, easily interpretable score makes it particularly useful for community members, policymakers, and environmental managers in addressing water quality issues in AMD-impacted regions.

Small Island Developing States (SIDS) comprise a group of 58 nations identified by the United Nations as facing unique sustainability challenges. These challenges include high exposure to climate change and a lack of data and limited resources. The effects of climate change are already observed in SIDS, notably an increase in the magnitude and frequency of natural disasters, biodiversity loss, ocean acidification, coral bleaching, sea-level rise, and coastal erosion. The coastal zone is considered to be the main economic, environmental, and cultural resource of SIDS, making them particularly vulnerable to the adverse effects of climate change. This project focuses on quantifying and disentangling coastal changes, including erosion, accretion and coastline stability. Existing literature lacks a comprehensive understanding of the patterns of coastal changes, as well as the main anthropogenic and environmental drivers involved. We address this research gap by quantifying the challenges that SIDS encounter, with a particular emphasis on coastal changes.The approach is data-driven, relying on observational time series extracted from remote sensing (e.g., Sentinel-2, Planet Scope, Landsat missions), in situ measurements (e.g., tide gauge data), and open-access databases. We have developed a robust method based on image segmentation to extract the island's shape over time, enabling us to illustrate the island's dynamics and obtain reliable time series of the coastline position. The main drivers of coastal changes are then identified and quantified using time series analysis methods, including causal inference and discovery methods, for SIDS worldwide. We place a specific focus on the Maldives (Indian Ocean) due to its low elevation and high human activity. Additionally, the methodology expands to investigate a spectrum of issues, including the impacts of human activities (e.g., land reclamation, sand mining, shoreline armouring) on the natural responses of coastlines, as well as the effects of confounding factors or common drivers (e.g., Indian monsoon, tropical cyclones, and El Niño/Southern Oscillation). The ultimate goal is to develop a spatiotemporal variable coastline vulnerability index by integrating socioeconomic and environmental time series data, facilitating the assessment of environmental policies in SIDS.

Very high resolution (VHR) mapping through remote sensing (RS) imagery presents a new opportunity to inform decision-making and sustainable practices in countless domains. Efficient processing of big VHR data requires automated tools applicable to numerous geographic regions and features. Contemporary RS studies address this challenge by employing deep learning (DL) models for specific datasets or features, which limits their applicability across contexts. The present research aims to overcome this limitation by introducing EcoMapper, a scalable solution to segment arbitrary features in VHR RS imagery. EcoMapper fully automates processing of geospatial data, DL model training, and inference. Models trained with EcoMapper successfully segmented two distinct features in a real-world UAV dataset, achieving scores competitive with prior studies which employed context-specific models. To evaluate EcoMapper, many additional models were trained on permutations of principal field survey characteristics (FSCs). A relationship was discovered allowing derivation of optimal ground sampling distance from feature size, termed Cording Index (CI). A comprehensive methodology for field surveys was developed to ensure DL methods can be applied effectively to collected data. The EcoMapper code accompanying this work is available at https://github.com/hcording/ecomapper .

The success of rehabilitating legacy or abandoned mines is highly dependent on engaging the community in the program. Although there is consensus among stakeholders that this line of enquiry and process is critically important, there is no coherent understanding of this concept. We reviewed the literature on engaging the community in the rehabilitation of legacy mines using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We accessed peer-reviewed publications from Scopus, Web of Science, and ProQuest databases. Upon application of a set of exclusion criteria, 53 articles were further considered for full analysis. Based on our results, we have established the continuum of involving the host community in the rehabilitation process, from information dissemination, consultation, engagement, partnership, and empowerment to leadership. Also, we have identified factors that influence rehabilitation programs, including policy, people, process, context, and mining processes. We discuss the implications of these findings, emphasizing the gaps that warrant further investigations.

Rising sea levels due to climate change are causing increased salinisation of low-lying coastal and floodplain soils, and the impact of this process on the bioavailability of plant nutrients needs to be understood as mitigation strategies are adapted. Zinc (Zn) is an element of particular importance due to its function as a micronutrient for plants including rice and other staple foods. In the current study, our aim was to investigate the effects of salinisation on zinc adsorption onto soils representing at-risk coastal and floodplain environments, addressing in particular our knowledge gap concerning the roles that solution chemistry and soil composition play. To this end, we conducted batch adsorption experiments in the laboratory and ran geochemical models in saline solutions up to 0.7 mol L-1 ion strength incorporating both (i) a multi surface model (MSM) for surface reactions containing three phases, that is iron hydroxides, organic matter and phyllosilicate clays, and (ii) aqueous-phase complexation to dissolved organic and inorganic ligands. Surface reactions were modelled using the diffuse double layer model, the NICA-Donnan model and an ion exchange model using the Gaines-Thomas convention. We combined the experimentally determined mass composition of surface phases with generic modelling parameters taken from the literature. We first show that increasing salinity enhances the formation of aqueous Zn-chloride complexes in the presence of dissolved organic matter and bicarbonate, thereby decreasing the availability of free Zn2+ and supressing the partitioning of zinc to the adsorbed phase. We demonstrate using batch adsorption experiments with a calcareous hydraquent and a tropaquept, that salinity decreases zinc adsorption strongly in the pH range between 3 and 6. Satisfactory agreement between experiments and model calculations was achieved with root-mean-square errors ranging for different salinities between 2.88% and 2.92% for the hydraquent and between 4.59% and 2.74% for the tropaquept soil. Model predictions of adsorption were slightly inferior at low salinity for the hydraquent soil and at high salinity for the tropaquept soil, pointing possibly to an incomplete geochemical model or to a need to parametrise surface adsorption models at higher ionic strengths. Present surface models have been largely parametrised at lower ionic strength. We lastly apply the MSM to examine zinc adsorption in five endoaquepts soils, representing soil series from Bangladesh. We show that increasing salinity decreases zinc adsorption to the soil organic matter and the clay fractions. We conclude from our findings that increased soil salinity due to rising sea levels and climate change will have a significant impact on zinc cycling and possibly other micronutrients in areas where coastal soils and floodplain soils overlap, such as deltas and estuaries. In particular, we predict a decrease in zinc adsorption in acidic to neutral soils. The availability of zinc for biouptake through the roots of crop plants including rice will be significantly disturbed following salinisation, most likely affecting crop production. Our study demonstrates the potential that geochemical modelling combined with experimental data has to improve our capability to assess the effects of salinity due to rising seawater levels in vulnerable regions of the world. Adsorption of zinc in tropical wetland soils is studied using batch experiments and geochemical modelling. The constructed multi-surface model uses soil organic matter, iron oxides and clay. The binding modes and mathematical models include adsorption with the NICA-Donnan model, surface complexation with the DDL model, and cation exchange with anion exchange model. image

Material flow analysis (MFA) is used to quantify and understand the life cycles of materials from production to end of use, which enables environmental, social, and economic impacts and interventions. MFA is challenging as available data are often limited and uncertain, leading to an under-determined system with an infinite number of possible stocks and flows values. Bayesian statistics is an effective way to address these challenges by principally incorporating domain knowledge, quantifying uncertainty in the data, and providing probabilities associated with model solutions. This paper presents a novel MFA methodology under the Bayesian framework. By relaxing the mass balance constraints, we improve the computational scalability and reliability of the posterior samples compared to existing Bayesian MFA methods. We propose a mass-based, child and parent process framework to model systems with disaggregated processes and flows. We show posterior predictive checks can be used to identify inconsistencies in the data and aid noise and hyperparameter selection. The proposed approach is demonstrated in case studies, including a global aluminum cycle with significant disaggregation, under weakly informative priors and significant data gaps to investigate the feasibility of Bayesian MFA. We illustrate that just a weakly informative prior can greatly improve the performance of Bayesian methods, for both estimation accuracy and uncertainty quantification.

Accurate and precise monitoring of coastal environments allows for the better preservation of their biodiversity. This study applies multispectral imaging, unmanned aerial vehicles (UAVs), and supervised and unsupervised techniques to characterize a coastal area in Batangas, Philippines. Multispectral image data was gathered using a DJI Mavic 3M drone. Afterwards, vegetation maps using NDVI, GNDVI, NDRE, and LCI were generated. Regions of the image were then clustered using the k-means clustering algorithm to define habitats in t he area of study. These clusters were then used to train supervised machine-learning algorithms for pixel-based image classification. After classifying the entire image with these models, the identified ha bitats we re characterized based on their associated vegetation index measurements. It was found that aquatic areas of the image possessed scores associated with healthy and photosynthetically active water.

The supergyre in the Southern Hemisphere is thought to connect the Atlantic, Indian, and Pacific subtropical gyres together. The aim of the study is to investigate whether the supergyre is identifiable in the Coupled Model Intercomparison Project Phase 6 (CMIP6) models and in the Estimating the Circulation and Climate of the Ocean (ECCO) reanalysis and to evaluate the influence of the supergyre on the properties of Antarctic Intermediate Water (AAIW), the dominant water mass at intermediate depths in the Southern Hemisphere. CMIP6 models and ECCO are in agreement at the surface with supergyres connected across all basins but present some differences at depth in both position and strength. AAIW core properties (temperature and salinity) present a high degree of similarity across basins within the supergyre but not outside of it. By the end of the century, the supergyre reduces in size and intensifies at intermediate depths, and the AAIW core depth warms in all basins and freshens in the Pacific although no clear trend in salinity can be found in the Atlantic and Indian basins in the SSP5-8.5 scenario. The high degree of similarity across basins within the supergyre is maintained in the future scenario. The results suggest that by connecting the basins together at intermediate depth, the supergyre plays a key role in circulating and homogenizing the AAIW core properties. Our results emphasize the role of the supergyre in circulating water masses at the surface and intermediate depths in CMIP6 models and hence its importance to the global circulation.

BACKGROUND:The Sto. Niño site in Benguet province, Philippines was once a mining area that has now been transformed into an agricultural land. In this area, there has been significant integration of the three indigenous people (IPs) Ibaloi, Kankanaeys and Kalanguyas with the Ilocano community. These IPs safeguard biodiversity and traditional knowledge, including medicinal plant use. However, the documentation of these plant species and their medicinal applications has not been systematic, with the resultant loss of knowledge across generations. This study aims to document the medicinal and ritual plants used by the indigenous communities at the site, in order to preserve and disseminate traditional medicinal knowledge that would otherwise be lost. METHODS:Ethnobotanical data were collected in Sto. Niño, Brgy. Ambassador, Municipality of Tublay, Benguet, Philippines, and collected through semi-structured interviews, together with focus group discussions (FGD). A total of 100 residents (39 male and 61 female) were interviewed. Among them, 12 were key interviewees, including community elders and farmers, while the rest were selected through the convenience and snowball technique. Demographic information collected from the interviewees included age, gender, and occupation. Ethnobotanical information collected focused on medicinal plants, including the specific parts of plants used, methods of preparation, modes of treatment, and the types of ailments treated. Ethnobotanical quantitative indices of the relative frequency of citations (RFC) and informant consensus factor (ICF) were calculated to evaluate the plant species that were utilized by the community. RESULTS:A total of 28 medicinal plants from 20 different families and 6 ritual plants from 5 different families were documented. Asteraceae, Poaceae, and Lamiaceae (10.71%) family are the most mentioned medicinal plant species, followed by Myrtaceae and Euphorbiaceae (7.14%). The most widely used growth form were herbs (46.4%), while leaves (61.5%) were the most utilized plant part, and the preparation of a decoction (62.2%) was the most preferred method of processing and application. The medicinal plants were most commonly utilized for wound-healing, cough and colds, stomachache and kidney trouble, whereas ritual plants were largely used for healing, protection, and funeral ceremonies. CONCLUSION:This study marks the first report on the medicinal and ritual plants used by a group of indigenous communities in Sto. Niño, Brgy. Ambassador, Tublay, Benguet Province. The data collected show that plant species belonging to the Asteraceae, Poaceae, and Lamiaceae family were the most mentioned and should be further evaluated by pharmacological analysis to assess their wider use for medicinal treatment.

The Maldives face the threat of tsunamis from a multitude of sources. However, the limited availability of critical data, such as bathymetry (a recurrent problem for many island nations), has meant that the impact of these threats has not been studied at an island scale. Conducting studies of tsunami propagation at the island scale but across multiple atolls is also a challenging task due to the large domain and high resolution required for modelling. Here we use a high-resolution bathymetry dataset of the Maldives archipelago, as well as corresponding high numerical model resolution, to carry out a scenario-based tsunami hazard assessment for the entire Maldives archipelago to investigate the potential impact of plausible far-field tsunamis across the Indian Ocean at the nearshore island scales across the atolls. The results indicate that the bathymetry of the atolls, which are characterized by very steep boundaries offshore, is extremely efficient in absorbing and redirecting incoming tsunami waves. Results also highlight the importance that local effects have in modulating tsunami amplitude nearshore, including the location of the atoll in question, the location of a given island within the atoll, and the distance of that island to the reef, as well as a variety of other factors. We also find that the refraction and diffraction of tsunami waves within individual atolls contribute to the maximum tsunami amplitude patterns observed across the islands in the atolls. The findings from this study contribute to a better understanding of tsunamis across complex atoll systems and will help decision and policy makers in the Maldives assess the potential impact of tsunamis across individual islands. An online tool is provided which presents users with a simple interface, allowing the wider community to browse the simulation results presented here and assess the potential impact of tsunamis at the local scale.

Abstract. The neodymium (Nd) isotopic composition of seawater is a widely used ocean circulation tracer. However, uncertainty in quantifying the global ocean Nd budget, particularly constraining elusive non-conservative processes, remains a major challenge. A substantial increase in modern seawater Nd measurements from the GEOTRACES programme, coupled with recent hypotheses that a seafloor-wide benthic Nd flux to the ocean may govern global Nd isotope distributions (εNd), presents an opportunity to develop a new scheme specifically designed to test these paradigms. Here, we present the implementation of Nd isotopes (143Nd and 144Nd) into the ocean component of the FAMOUS coupled atmosphere–ocean general circulation model (Nd v1.0), a tool which can be widely used for simulating complex feedbacks between different Earth system processes on decadal to multi-millennial timescales. Using an equilibrium pre-industrial simulation tuned to represent the large-scale Atlantic Ocean circulation, we perform a series of sensitivity tests evaluating the new Nd isotope scheme. We investigate how Nd source and sink and cycling parameters govern global marine εNd distributions and provide an updated compilation of 6048 Nd concentrations and 3278 εNd measurements to assess model performance. Our findings support the notions that reversible scavenging is a key process for enhancing the Atlantic–Pacific basinal εNd gradient and is capable of driving the observed increase in Nd concentration along the global circulation pathway. A benthic flux represents a major source of Nd to the deep ocean. However, model–data disparities in the North Pacific highlight that under a uniform benthic flux, the source of εNd from seafloor sediments is too non-radiogenic in our model to be able to accurately represent seawater measurements. Additionally, model–data mismatch in the northern North Atlantic alludes to the possibility of preferential contributions from “reactive” non-radiogenic detrital sediments. The new Nd isotope scheme forms an excellent tool for exploring global marine Nd cycling and the interplay between climatic and oceanographic conditions under both modern and palaeoceanographic contexts.

Successful rehabilitation of legacy mines continues to be challenging due to the tensions between legal requirements, current practices, and host communities' aspirations.Previous rehabilitation efforts have often focused on technical and environmental aspects, leading to their narrow focus that usually creates resistance from the host community and, thus, are usually unsustainable.To address these issues, particularly the lack of community engagement, we developed the Biodiversity Positive Mining for The Net Zero Challenge (Bio+Mine) project, which focuses on the abandoned Sto.Niño copper mine (Tublay, Benguet, Philippines).Before undertaking site sampling, our Social Science Team embarked on an extensive community engagement program to secure permits from the local inhabitants and the associated administrative and regulatory units.