A multi-framework analysis of stakeholders' perceptions in developing a localized blue carbon ecosystems strategy in Eastern Samar, Philippines

Blue carbon ecosystems (BCEs) are vital for global climate change mitigation and offer diverse local ecosystem co-benefits. Despite existing literatures on integrating national and international BCE agendas at the local level, the development and implementation of localized BCE strategies often lag behind. To provide insights on this knowledge gap, we present a case study conducted in Eastern Samar, Philippines. Employing a multi-framework analysis- encompassing DPSIR (drivers, pressures, state, impact, responses), SOAR (strengths, opportunities, aspirations, results), and PESTLE (political, economic, social, technological, legal, environmental) frameworks, stakeholder perceptions collected from focus group discussions highlight issues and challenges in developing and implementing a BCE strategy. Findings reveal that the aftermath of Typhoon Haiyan in 2013 in the study sites stimulated conservation efforts and raised awareness, but governance structures and policy enforcement influence the success and longevity of management and conservation efforts. Through the integration of multiple frameworks, this study outlined a potential localized BCE strategy, emphasizing both internal priorities such as stakeholder engagement and alternative livelihoods and external priorities related to policy and technological supports. While developed based on a specific case study in the Philippines, the proposed strategy is presented in a general manner, enabling its potential replication in other provinces in the Philippines or in countries with similar geographic settings.

Blue carbon storage in a tropical coastal estuary: Insights for conservation priorities

Seagrass ecosystems have been determined as necessary sinks in the global carbon cycle and contribute towards climate change mitigations. In the recent past, there has been an increase of studies focused on blue carbon opportunities provided by seagrasses but large knowledge gaps and uncertainties remain, particularly in tropical seagrass meadows in the South Asian regions. Therefore, the current study aims to quantify the organic carbon stocks in the seagrass meadows on the tropical estuary in southern coast of Sri Lanka and highlights the need of conserving seagrasses specially in the context of effective management of lagoons to achieve Sustainable Development Goals. Landsat 9 (OLI/TIRS) images were used to develop seagrass distribution maps for 2022 and the data were verified with ground truthing. Vegetation and soil samples were taken from eight sampling locations representing the Rekawa Lagoon. Aboveground biomass (AGB) and belowground biomass (BGB) were determined by multiplying the biomass with the carbon conversion factor whereas the loss-on-ignition (LOI) technique was applied to calculate the soil organic carbon. Results revealed that the soil core carbon content of the study site were ranged between 2.56 ± 0.29 to 3.04 ± 0.44 Mg C/ha. The calculated total carbon content of the 0.0324 km2 study area in Rekawa Lagoon was 10.21 Mg C, giving 87.06 % contribution from sediment organic carbon pool. This study provides insights for the conservation of these critical ecosystems and highlights the need of policy and action agendas for better management.

Understanding the depth limit of the seagrass Cymodocea nodosa as a critical transition: Field and modeling evidence

Changes in light and sediment conditions can sometimes trigger abrupt regime shifts in seagrass meadows resulting in dramatic and unexpected die-offs of seagrass. Light attenuates rapidly with depth, and in seagrass systems with non-linear behaviours, can serve as a sharp boundary beyond which the meadow transitions to bare sand. Determining system behaviour is therefore essential to ensuring resilience is maintained and to prevent stubborn critical ecosystem transitions caused by declines in water quality. Here we combined field and modelling studies to explore the transition from meadow to bare sand in the seagrass Cymodocea nodosa at the limit of its depth distribution in a shallow, light-limited bay. We first describe the relationship between light availability and seagrass density along a depth gradient in an extensive unfragmented meadow (Alfacs bay, NE Spain). We then develop a simple mechanistic model to characterise system behaviour. In the field, we identified sharp decline in shoot density beyond a threshold of ∼1.9 m depth, shifting from a vegetated state to bare sand. The dynamic population model we developed assumes light-dependent growth and an inverse density-dependent mortality due to facilitation between shoots (mortality rate decreases as shoot density increases). The model closely tracked our empirical observations, and both the model and the field data showed signs of bistability. This strongly suggests that the depth limit of C. nodosa is a critical transition driven by photosynthetic light requirements. While the mechanisms still need to be confirmed with experimental evidence, recognizing the non-linear behaviour of C. nodosa meadows is vital not only in improving our understanding of light effects on seagrass dynamics, but also in managing shallow-water meadows. Given the shallow threshold (<2m), light-limited systems may experience significant and recalcitrant meadow retractions with even small changes in sediment and light conditions. Understanding the processes underlying meadow resilience can inform the maintenance and restoration of meadows worldwide.

Using UAV and Field Measurement Technology to Monitor the Impact of Coal Gangue Pile Temperature on Vegetation Ecological Construction

Coal gangue is an inevitable product in coal mining and processing and is the most important source of pollution in mines. Vegetation restoration of coal gangue piles must consider its special site conditions. Therefore, we conducted unmanned air vehicle (UAV) temperature monitoring, field investigation and experimental analysis on spontaneous combustion coal gangue piles in Lu’an mining area. In the vegetation construction of coal gangue piles, high-temperature stress affects plant survival. The spontaneous combustion coal gangue piles have abnormal temperature, high surface temperature and few vegetation types. The plant community species diversity index (Shannon–Wiener index, Pielou’s index and Species abundance index) is small, the plant community is single and the plant diversity is low. Spontaneous combustion of coal gangue leads to soil acidification, reducing soil water content, soil organic carbon (SOM), available nitrogen (AN), available potassium (AK) and available phosphorus (AP). These factors are single or interactive in plants and have an impact on plant survival and growth. The research results are of great significance to the vegetation restoration of spontaneous combustion coal gangue piles, ecological reconstruction and the improvement of the ecological environment of coal mine areas.

Assessment of State Transition Dynamics of Coastal Wetlands in Northern Venice Lagoon, Italy

Coastal wetlands represent particularly valuable natural resources, characterized by the interaction between their geomorphological and biological components. Their adaptation to the changing conditions depends on the rate and extent of spatial and temporal processes and their response is still not fully understood. This work aims at detecting and improving the understanding of the transition dynamics on eco-geomorphological structures in a coastal wetland ecosystem. The approach could support sustainable habitat management improving the detection and optimizing the offer of Earth Observation (EO) products for coastal system monitoring. Such course of action will strengthen evidence-based policy making, surface biophysical data sovereignty and the Space Data downstream sector through remote sensing techniques thanks to the capability of investigating larger scale and short-to-long-term dynamics. The selected case study is the Lido basin (Venice Lagoon, Italy). Our methodology offers a support in the framework of nature-based solutions, allowing the identification of ecosystem-level indicators of the surface biophysical properties influencing stability and evolution of intertidal flats on which a conceptual model is implemented. Landsat satellite imagery is used to delineate the spatial and temporal variability of the main vegetation and sediment typologies in 1990–2011. Within this period, specific anthropic activities were carried out for morphological restoration and flood protection interventions. Specifically, the lower saltmarsh shows its more fragmented part in the Baccan islet, a residual sandy spit in front of the Lido inlet. The area covered by Sarcocornia-Limonium, that triggers sediment deposition, has fluctuated yearly, from a minimum coverage of 13% to a maximum of 50%. The second decade (2001–2009) is identified as the period with major changes of halophytic and Algae-Biofilm cover typologies distribution. The power law and related thresholds, representing the patch size frequency distribution, is an indicator of the ecosystem state transition dynamics. The approach, based on multi-temporal and spatial EO analysis, is scalable elsewhere, from regional to local-to-global scale, considering the variability of climate data and anthropogenic activities. The present research also supports sustainable habitat management, improving the detection, and optimizing the offer of EO products for coastal system monitoring.

Implications of macroalgae blooms to the spatial structure of seagrass seascapes: The case of the Anadyomene spp. (Chlorophyta) bloom in Biscayne Bay, Florida

Macroalgal blooms are becoming an increasing problem in coastal regions worldwide and have been associated with a widespread decline of seagrass habitats. It is critical to measure macroalgal bloom (MB) impacts at broad spatial scales since seagrass seascape characteristics can influence feedback processes that regulate the resilience of seagrass ecosystems. We assessed the broad-scale spatial impacts of an MB formed by Anadyomene spp. on the seagrass seascapes in Biscayne Bay (Miami, US) using a multi-scale seascape approach. By integrating field and remote sensing data, our multi-scale approach showed significant reductions in seagrass foliage cover and a seascape structure transformation across the bloom extent. The landscape cover and patch extensiveness declined after the MB peak. Other spatial pattern metrics also showed that the seagrass seascape structure got fragmented. We demonstrated that a persistent MB could transform the structure of seagrass seascapes, hindering the resilience of seagrass habitats.

The fundamental role of ecological feedback mechanisms for the adaptive management of seagrass ecosystems - a review

Seagrass meadows are vital ecosystems in coastal zones worldwide, but are also under global threat. One of the major hurdles restricting the success of seagrass conservation and restoration is our limited understanding of ecological feedback mechanisms. In these ecosystems, multiple, self-reinforcing feedbacks can undermine conservation efforts by masking environmental impacts until the decline is precipitous, or alternatively they can inhibit seagrass recovery in spite of restoration efforts. However, no clear framework yet exists for identifying or dealing with feedbacks to improve the management of seagrass ecosystems. Here we review the causes and consequences of multiple feedbacks between seagrass and biotic and/or abiotic processes. We demonstrate how feedbacks have the potential to impose or reinforce regimes of either seagrass dominance or unvegetated substrate, and how the strength and importance of these feedbacks vary across environmental gradients. Although a myriad of feedbacks have now been identified, the co-occurrence and likely interaction among feedbacks has largely been overlooked to date due to difficulties in analysis and detection. Here we take a fundamental step forward by modelling the interactions among two distinct above- and belowground feedbacks to demonstrate that interacting feedbacks are likely to be important for ecosystem resilience. On this basis, we propose a five-step adaptive management plan to address feedback dynamics for effective conservation and restoration strategies. The management plan provides guidance to aid in the identification and prioritisation of likely feedbacks in different seagrass ecosystems.

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear, because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a "theory of everything" for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

A framework for the resilience of seagrass ecosystems

Seagrass ecosystems represent a global marine resource that is declining across its range. To halt degradation and promote recovery over large scales, management requires a radical change in emphasis and application that seeks to enhance seagrass ecosystem resilience. In this review we examine how the resilience of seagrass ecosystems is becoming compromised by a range of local to global stressors, resulting in ecological regime shifts that undermine the long-term viability of these productive ecosystems. To examine regime shifts and the management actions that can influence this phenomenon we present a conceptual model of resilience in seagrass ecosystems. The model is founded on a series of features and modifiers that act as interacting influences upon seagrass ecosystem resilience. Improved understanding and appreciation of the factors and modifiers that govern resilience in seagrass ecosystems can be utilised to support much needed evidence based management of a vital natural resource.

Identifying habitats at risk: simple models can reveal complex ecosystem dynamics

The relationship between ecological impact and ecosystem structure is often strongly nonlinear, so that small increases in impact levels can cause a disproportionately large response in ecosystem structure. Nonlinear ecosystem responses can be difficult to predict because locally relevant data sets can be difficult or impossible to obtain. Bayesian networks (BN) are an emerging tool that can help managers to define ecosystem relationships using a range of data types from comprehensive quantitative data sets to expert opinion. We show how a simple BN can reveal nonlinear dynamics in seagrass ecosystems using ecological relationships sourced from the literature. We first developed a conceptual diagram by cataloguing the ecological responses of seagrasses to a range of drivers and impacts. We used the conceptual diagram to develop a BN populated with values sourced from published studies. We then applied the BN to show that the amount of initial seagrass biomass has a mitigating effect on the level of impact a meadow can withstand without loss, and that meadow recovery can often require disproportionately large improvements in impact levels. This mitigating effect resulted in the middle ranges of impact levels having a wide likelihood of seagrass presence, a situation known as bistability. Finally, we applied the model in a case study to identify the risk of loss and the likelihood of recovery for the conservation and management of seagrass meadows in Moreton Bay, Queensland, Australia. We used the model to predict the likelihood of bistability in 23 locations in the Bay. The model predicted bistability in seven locations, most of which have experienced seagrass loss at some stage in the past 25 years providing essential information for potential future restoration efforts. Our results demonstrate the capacity of simple, flexible modeling tools to facilitate collation and synthesis of disparate information. This approach can be adopted in the initial stages of conservation programs as a low-cost and relatively straightforward way to provide preliminary assessments of.nonlinear dynamics in ecosystems.

Coastal retreat and improved water quality mitigate losses of seagrass from sea level rise

The distribution and abundance of seagrass ecosystems could change significantly over the coming century due to sea level rise (SLR). Coastal managers require mechanistic understanding of the processes affecting seagrass response to SLR to maximize their conservation and associated provision of ecosystem services. In Moreton Bay, Queensland, Australia, vast seagrass meadows supporting populations of sea turtles and dugongs are juxtaposed with the multiple stressors associated with a large and rapidly expanding human population. Here, the interactive effects of predicted SLR, changes in water clarity, and land use on future distributions of seagrass in Moreton Bay were quantified. A habitat distribution model of present day seagrass in relation to benthic irradiance and wave height was developed which correctly classified habitats in 83% of cases. Spatial predictions of seagrass and presence derived from the model and bathymetric data were used to initiate a SLR inundation model. Bathymetry was iteratively modified based on SLR and sedimentary accretion in seagrass to simulate potential seagrass habitat at 10 year time steps until 2100. The area of seagrass habitat was predicted to decline by 17% by 2100 under a scenario of SLR of 1.1 m. A scenario including the removal of impervious surfaces, such as roads and houses, from newly inundated regions, demonstrated that managed retreat of the shoreline could potentially reduce the overall decline in seagrass habitat to just 5%. The predicted reduction in area of seagrass habitat could be offset by an improvement in water clarity of 30%. Greater improvements in water clarity would be necessary for larger magnitudes of SLR. Management to improve water quality will provide present and future benefits to seagrasses under climate change and should be a priority for managers seeking to compensate for the effects of global change on these valuable habitats.