Competitive interactions between invasive Phragmites australis and Spartina alterniflora: Mechanisms and management implications for marsh migration

Constructing Worst-Scenario typhoon storm surge in a changing climate by 2040s: The typhoon Mangkhut (2018) simulations in Hong Kong

Modelling the geomorphological evolution of coastal wetlands under rising sea levels: A reduced dimensional and multi-temporal evaluation

River-sea interaction-regulated spatial distribution and source apportionment of mercury in the soil of the Yellow River Estuary coastal wetland.

Vulnerability of mangrove resources to sea-level rise on Sanibel Island, Florida, USA

Biological processes dominate the dynamic changes in the dissolved inorganic carbon ion equilibrium system of coastal wetlands under tidal influence.

Hydrodynamics and short-term morphodynamics of hybrid terrace configuration in a tidally restored impoundment subject to relative sea-level rise

Persistent Cenozoic sea-level rise: Historical evidence from sequence-stratigraphic and sedimentary facies studies in continental margin basins

It is well known that sea level rise (SLR) will force retreat along rural coastlines but that cities will need to protect their coasts. But how exactly should seawalls, flood insurance, and retreat be used over time to minimize the overall cost of coastal flooding to society? This paper examines dynamic coastal adaptation in six cities along the eastern seaboard of the United States through 2180. We argue that seawalls should be designed to minimize the sum of seawall costs and expected residual flood damage. Flood insurance for residual damage can address risk aversion. The results reveal that only areas with high expected damage per kilometer of coastline require walls. Only a few segments of most cities need a wall now. The optimal wall height is about 1-2m. SLR will force more urban seawalls to be built over the next 100 years. The faster SLR rises, the sooner they will need to be built.

Despite its strong influence on relative sea-level (RSL) rise, there is still low confidence in estimates of vertical land motion (VLM) and its contribution to RSL change. To address this problem, we synergize diverse VLM data, which now cover almost 65% of the coastal population, and are key to resolve small scale subsidence, including East, South, and Southeast Asian cities and populated deltaic regions, largely not covered by earlier geodetic measurements. We find that the average modern (1995-2020) global RSL rise experienced by coastal populations (6 mm/year) is about twice the climate-driven absolute sea-level rise. This reflects a strong tendency for higher rates of subsidence in densely populated areas, with 71% of the global coastal population living in subsiding regions. Paired with community efforts to extend consistent observations, these data are essential to ensure reliable estimates of present and future RSL rise to support risk and adaptation assessment.

Sea-level rise threats to food security: A review of agrifood system resilience in the Lower Fraser Valley, BC.

Despite mitigation efforts, anthropogenic emissions are projected to cause a global mean sea level rise of approximately 0.44 m and sustained sea levels over human timescales (e.g., centuries). Even without glacial melting, sea level remains elevated for centuries due to the substantial thermal inertia of the ocean interior. However, mechanisms governing persistent sea level rise remain inadequately understood. Here, using a fully coupled climate model, we demonstrate that a distinct sea surface temperature pattern drives enhanced and prolonged sea level rise. This surface warming pattern enhances the absorption of shortwave radiation through climate feedbacks, such as low cloud and sea ice-albedo feedbacks, thereby sustaining ocean heat uptake, thermal expansion, and continued sea level rise. Atmosphere-only simulations confirm that the sea surface temperature pattern alone explains the increased shortwave radiation through the positive feedbacks. These findings underscore the importance of accurately representing surface warming patterns and associated cloud responses in future sea level rise projections.

Climate change is a global phenomenon that requires collective intervention if humanity is to survive its catastrophic effects. The effects of climate change are palpable the world over, particularly in the rising of temperatures and sea levels and the snow melt and heavy rains that cause severe flooding followed by drought. It has been argued that climate change is a result, or consequence, of a lack of environmental awareness that is anthropogenic in nature. Of course, there are other causes of climate change that are not anthropogenic; there are natural causes too. However, these debates have tended to be dominated and led by extra-African scholars and activists, not that there are no African scholars and activists on climate change and related phenomena. This has created an illusion that Africa’s agency on climate change debates, and possible solutions, is hampered and curtailed. The article interrogates Africa’s agency on the climate change debates proffered thus far. Furthermore, it amplifies African and Africa’s voices on climate change. More importantly, this article seeks to articulate Africa’s positionality on climate change. The article uses a qualitative research methodology that allows for the interpretation of primary and secondary sources.

Microbially driven iron redox cycling dominates Fe-bound organic carbon formation in coastal wetlands under sea level rise.

ABSTRACT This article examines the intertwined dynamics of ecological precarity and coastal erosion in Trespassing by Uzma Aslam Khan, situating the narrative within the broader context of indigenous vulnerability in coastal Pakistan. It argues that the novel foregrounds forms of indigenous ecoprecarity produced through the overlapping forces of climate change, uneven development, and historical marginalisation. It engages postcolonial ecocritical debates advanced by Elizabeth DeLoughrey, Dipesh Chakrabarty, Vandana Shiva, Shazia Rahman, and Pramod K. Nayar to situate contemporary environmental challenges within the longer histories of European imperialism and industrialisation in South Asia. The article examines how colonial regimes transformed landscapes into sites of extraction, fostering exploitative attitudes toward nature that persist today and contribute to rising sea levels, floods, droughts, and shoreline erosion. Furthermore, it explores how environmental instability is represented in literary form, presenting the shoreline as a shifting boundary and highlighting how communities interpret, endure, and negotiate ecological change.

Coastal regions in Indonesia are currently facing unprecedented risks from the convergence of global climatic shifts and localized geological instability. This study investigates the intensifying vulnerability of the Jakarta-Bekasi coastal corridor, highlighting it as a critical zone within the broader context of regional climate adaptation. The objective is to evaluate the synergistic impact of eustatic sea-level rise and aggressive land subsidence on permanent inundation projections through 2030. Utilizing a quantitative geospatial design, the research integrates satellite altimetry from the Sentinel-6 mission with terrestrial geodetic data from 12 Continuous Operating Reference Stations (CORS) across a 12,500-hectare study area. Key variables include vertical land motion rates and sea surface height anomalies, processed through high-resolution Digital Elevation Models (DEMNAS). Results indicate that localized land subsidence, peaking at 11.2 cm per year, is the primary driver of flood risk, rendering Relative Sea Level Rise () significantly more destructive than global eustatic averages. Statistical analysis confirms that subsidence accounts for 82% of the variance in coastal inundation expansion, with critical hotspots in the Penjaringan and Muara Gembong sectors. These findings imply that current coastal defense structures are nearing functional failure due to the rapid erosion of operational freeboards. Consequently, the study concludes that regional resilience necessitates a shift from static engineering to adaptive water management and the implementation of Nature-based Solutions. Future research should prioritize AI-driven predictive modeling and volumetric building load analysis to enhance long-term mitigation strategies.

This paper develops a stochastic optimal control framework for modeling age-structured population dynamics under climate-induced migration, with application to Nigeria’s Niger Delta region. Climate-related slow-onset and extreme hazards, including flooding, sea-level rise, and environmental degradation, drive internal displacement that disproportionately affects younger working-age groups and intensifies urban demographic pressure and infrastructure strain. The proposed model extends the deterministic McKendrick–von Foerster equation into a stochastic partial integro-differential system by incorporating a climate-sensitive migration kernel with multiplicative Wiener noise to represent persistent uncertainty and optional Lévy jumps to capture abrupt extreme events. Policy interventions, including relocation incentives, infrastructure capacity enhancements, and adaptive zoning, are formulated as controls to minimize an expected long-term cost functional that penalizes demographic imbalances, intervention effort, and migration-related disruptions. Optimality conditions are derived from an adapted stochastic Pontryagin maximum principle in infinite-dimensional spaces, resulting in a forward–backward stochastic partial differential equation system. The well-posedness of the state dynamics is proven using semigroup theory and fixed-point methods, the existence of optimal controls is established through compactness and continuity arguments, and long-term ergodic behavior under persistent noise is analyzed using Lyapunov functionals. Numerical solutions combine finite-difference discretization of the age variable, Euler–Maruyama time-stepping, and Monte Carlo integration for stochastic terms, with convergence demonstrated under Lipschitz and stability assumptions. A case study in Rivers State, centered on Port Harcourt and involving an estimated population of approximately 7 million, is calibrated using UN World Population Prospects age distributions, World Bank Groundswell Africa internal climate migration projections, and regional flood probability estimates. Simulations indicate that stochastic optimal policies reduce expected urban demographic overload variance by 20–35% relative to deterministic baselines under representative flood scenarios, while promoting more balanced age structures and supporting resilient urban planning. The study contributes to environmetrics by advancing uncertainty quantification for climate-induced migration modeling and provides a reproducible Python-based decision-support framework for evidence-based policy in climate-vulnerable coastal developing regions.

Coastal regions played a key role in the emergence of Early Neolithic cultures. Fluctuating sea levels shaped prehistoric human migration, settlement patterns, and adaptation strategies. The lower reaches of the Min River in Fujian were a major centre of activity. During the Middle to Late Neolithic, marine communities such as the Keqiutou (6500–5500 cal. a BP) and Tanshishan (5500–4300 cal. a BP) cultures flourished. However, the scarcity of earlier remains has limited understanding of Early Neolithic life before 8000 cal. a BP. We dated stratigraphic layers at the newly excavated Niutoushan site using radiocarbon dating and optically stimulated luminescence (OSL). OSL results indicate the site’s Neolithic culture layer between 9.3 ± 0.7 ka and 8.1 ± 0.5 ka, with radiocarbon dates clustering around 8300–7000 cal. a BP. Based on the younger bounds of the dating results and kernel density estimation, the Neolithic remains at the site are dated to approximately 8000–7000 cal. a BP, identifying Niutoushan as one of the earliest Neolithic sites in the region. Combined with sea-level reconstructions, the findings suggest that the rapid Early Holocene sea-level rise drove human migration along China’s eastern coast before 8000 cal. a BP. The Niutoushan culture was influenced by Neolithic cultures from northern coastal regions and potentially by those located to its south across the exposed Taiwan Strait from the Last Glacial Maximum to the Early Holocene. This points to complex interactions among Early Neolithic cultures in both northern and southern coastal China, warranting further investigation for validation.

Abstract Recent advances in modeling 21st‐century sea‐level rise (SLR) and its associated societal outcomes have demonstrated that the spatial pattern of SLR combined with highly variable population density along global coastlines exert a strong control on its impacts. Here, we extend this research by examining differential costs arising from two sources of SLR that exhibit distinct spatial “fingerprints”—mass flux from the Antarctic (AIS) and Greenland (GrIS) Ice Sheets. To do this, we employ the DSCIM‐Coastal data and modeling platform to quantify flood extents and population exposure to inundation from sea‐level changes associated with an ensemble of Ice Sheet Model Intercomparison Project projections between 2015 and 2100 CE. We also introduce the Social Cost of Ice Sheet Mass loss (SC‐ISM) metric and calculate this for both AIS and GrIS mass loss scenarios. Due to the distinct sea‐level fingerprints of the two ice sheets, we find that mass flux from the AIS floods a larger area and would inundate a greater (present‐day) population than an equivalent mass flux from the GrIS and yields a substantially higher SC‐ISM. Across a suite of future climate scenarios, the global SC‐ISM associated with AIS mass loss is ∼30% higher than that of GrIS, driven largely by differential SLR rates along North Atlantic coastlines. However, across both ice sheet mass loss scenarios as well as a uniform SLR scenario, the SC‐ISM exhibits disproportionate impacts. In other words, when normalized by local Gross Domestic Product, low‐income regions experience a greater economic burden than high‐income regions, regardless of SLR source.

Predicting blue carbon sequestration in Sundarban coastal mangroves: A spatially explicit approach with INVEST and machine learning to advance climate resilience and UN SDG-aligned nature-based climate solutions.