Agriculture, meteorological, and hydrological drought is a natural hazard which affects ecosystems in the central India of Maharashtra state. Due to limited historical data for drought monitoring and forecasting available in the central India of Maharashtra state, implementing machine learning (ML) algorithms could allow for the prediction of future drought events. In this paper, we have focused on the prediction accuracy of meteorological drought in the semi-arid region based on the standardized precipitation index (SPI) using the random forest (RF), random tree (RT), and Gaussian process regression (GPR-PUK kernel) models. A different combination of machine learning models and variables has been performed for the forecasting of metrological drought based on the SPI-6 and 12 months. Models were developed using monthly rainfall data for the period of 2000-2019 at two meteorological stations, namely, Karanjali and Gangawdi, each representing a geographical region of Upper Godavari river basin area in the central India of Maharashtra state which frequently experiences droughts. Historical data from the SPI from 2000 to 2013 was processed to train the model into machine learning model, and the rest of the 2014 to 2019-year data were used for testing to forecast the SPI and metrological drought. The mean square error (MSE), root mean square error (RMSE), adjusted R2, Mallows' (Cp), Akaike's (AIC), Schwarz's (SBC), and Amemiya's PC were used to identify the best combination input model and best subregression analysis for both stations of SPI-6 and 12. The correlation coefficient ([Formula: see text]), mean absolute error (MAE), root mean square error (RMSE), relative absolute error (RAE), and root relative squared error (RRSE) were used to perform evaluation for SPI-6 and 12 months of both stations with RF, RT, and GPR-PUK kernel models during the training and testing scenarios. The results during testing phase revealed that the RF was found as the best model in forecasting droughts with values of [Formula: see text], MAE, RMSE, RAE (%), and RRSE (%) being 0.856, 0.551, 0.718, 74.778, and 54.019, respectively, for SPI-6 while 0.961, 0.361, 0.538, 34.926, and 28.262, respectively, for SPI-12 scales at Gangawdi station. Further, the respective values of evaluators at Karanjali station were 0.913 and 0.966, 0.541 and 0.386, 0.604 and 0.589, 52.592 and 36.959, and 42.315 and 31.394 for PUK kernel and RT models, respectively, during SPI-6 and SPI-12. Machine learning models are potential drought warning techniques because they take less time, have fewer inputs, and are less sophisticated than dynamic or scientific models.
Microplastic (MP) pollution is a major global issue that poses serious threats to aquatic organisms. Although research on MP pollution has been extensive, the relationship between MPs and water quality parameters in estuarine water systems is unclear. This work studied the spatiotemporal distribution and characteristics of MPs in the Karnaphuli River estuary, Bangladesh. MP abundance was calculated by towing with a plankton net (300 μm mesh size) at three river gradients (up-, mid- and downstream) and the association between physicochemical parameters of water (temperature, pH, salinity, electrical conductivity, total dissolved solids, and dissolved oxygen) and MP distribution patterns was also investigated. Mean MP abundance in water was higher during the wet season (April) (4.33 ± 2.45 items per m3) compared to the dry season (September) (3.65 ± 2.54 items per m3). In descending order, the highest MP abundance was observed downstream (6.60 items per m3) > midstream (3.15 items per m3) > upstream (2.22 items per m3). pH during the wet season (April) and temperature during the dry season (September) were key physicochemical parameters that correlated with river MP abundance (r = -0.74 and 0.74 respectively). Indicating that if the Karnaphuli River water has low pH or high temperature, there is likely to be high MPs present in the water. Most MP particles were film-shaped, white in color, and 1-5 mm in size. Of the six polymers detected, polypropylene (PP), polystyrene (PS), polyethylene terephthalate (PET), and cellulose were predominant, comprising roughly 17-19% each. These results can be used to model MP transport in the freshwater ecosystem of the Karnaphuli River estuary in Bangladesh to help develop future mitigation strategies.
Polyethylene terephthalate (PET) is one of the most produced plastics globally and its accumulation in the environment causes harm to the ecosystem. Polyethylene terephthalate hydrolyse (PETase) is an enzyme that can degrade PET into its monomers. However, free PETase lacks operational stabilities and is not reusable. In this study, development of cross-linked enzyme aggregate (CLEA) of PETase using amylopectin (Amy) as cross-linker was introduced to solve the limitations of free PETase. PETase-Amy-CLEA exhibited activity recovery of 81.9 % at its best immobilization condition. Furthermore, PETase-Amy-CLEA exhibited 1.37-, 2.75-, 2.28- and 1.36-fold higher half-lives than free PETase at 50 °C, 45 °C, 40 °C and 35 °C respectively. Moreover, PETase-Amy-CLEA showed broader pH stability from pH 5 to 10 and could be reused up to 5 cycles. PETase-Amy-CLEA retained >70 % of initial activity after 40 days of storage at 4 °C. In addition, lower Km of PETase-Amy-CLEA indicated better substrate affinity than free enzyme. PETase-Amy-CLEA corroded PET better and products yielded was 66.7 % higher than free PETase after 32 h of treatment. Hence, the enhanced operational stabilities, storage stability, reusability and plastic degradation ability are believed to make PETase-Amy-CLEA a promising biocatalyst in plastic degradation.
In tropical regions, different species of fiddler crabs coexist on the mangrove floor, which sometimes makes it difficult to define species-specific habitat by visual inspection. The aim of this study is to find key environmental parameters which affect the distribution of fiddler crabs and to determine the habitats in which each species was most abundant. Crabs were collected from 19 sites within the mudflats of Sepang-Lukut mangrove forest. Temperature, porewater salinity, organic matter, water content, carbon and nitrogen content, porosity, chlorophyll content, pH, redox potential, sediment texture and heavy metals were determined in each 1 m2 quadrate. Pearson correlation indicated that all sediment properties except pH and redox potential were correlated with sediment grain size. Canonical correspondence analysis (CCA) indicated that Uca paradussumieri was negatively correlated with salinity and redox potential. Sand dwelling species, Uca perplexa and Uca annulipes, were highly dependent on the abundance of 250 μm and 150 μm grain size particles in the sediment. Canonical Discriminative Analysis (CDA) indicated that variation in sediment grain size best explained where each crab species was most abundant. Moreover, U. paradussumieri commonly occupies muddy substrates of low shore, while U. forcipata lives under the shade of mangrove trees. U. annulipes and U. perplexa with the high number of spoon tipped setae on their second maxiliped are specialized to feed on the sandy sediments. U. rosea and U. triangularis are more common on muddy sediment with high sediment density. In conclusion, sediment grain size that influences most sediment properties acts as a main factor responsible for sediment heterogeneity. In this paper, the correlation between fiddler crab species and environmental parameters, as well as the interaction between sediment characteristics, was explained in order to define the important environmental factors in fiddler crab distributions.
Multibeam echosounders (MBES) are increasingly becoming the tool of choice for marine habitat mapping applications. In turn, the rapid expansion of habitat mapping studies has resulted in a need for automated classification techniques to efficiently map benthic habitats, assess confidence in model outputs, and evaluate the importance of variables driving the patterns observed. The benthic habitat characterisation process often involves the analysis of MBES bathymetry, backscatter mosaic or angular response with observation data providing ground truth. However, studies that make use of the full range of MBES outputs within a single classification process are limited. We present an approach that integrates backscatter angular response with MBES bathymetry, backscatter mosaic and their derivatives in a classification process using a Random Forests (RF) machine-learning algorithm to predict the distribution of benthic biological habitats. This approach includes a method of deriving statistical features from backscatter angular response curves created from MBES data collated within homogeneous regions of a backscatter mosaic. Using the RF algorithm we assess the relative importance of each variable in order to optimise the classification process and simplify models applied. The results showed that the inclusion of the angular response features in the classification process improved the accuracy of the final habitat maps from 88.5% to 93.6%. The RF algorithm identified bathymetry and the angular response mean as the two most important predictors. However, the highest classification rates were only obtained after incorporating additional features derived from bathymetry and the backscatter mosaic. The angular response features were found to be more important to the classification process compared to the backscatter mosaic features. This analysis indicates that integrating angular response information with bathymetry and the backscatter mosaic, along with their derivatives, constitutes an important improvement for studying the distribution of benthic habitats, which is necessary for effective marine spatial planning and resource management.
Tropical forests are highly diverse systems involving extraordinary numbers of interactions between species, with each species responding in a different way to the abiotic environment. Understanding how these systems function and predicting how they respond to anthropogenic global change is extremely challenging. We argue for the necessity of 'whole-ecosystem' experimental manipulations, in which the entire ecosystem is targeted, either to reveal the functioning of the system in its natural state or to understand responses to anthropogenic impacts. We survey the current range of whole-ecosystem manipulations, which include those targeting weather and climate, nutrients, biotic interactions, human impacts, and habitat restoration. Finally we describe the unique challenges and opportunities presented by such projects and suggest directions for future experiments.
Climate change manifestation in the ocean, through warming, oxygen loss, increasing acidification, and changing particulate organic carbon flux (one metric of altered food supply), is projected to affect most deep-ocean ecosystems concomitantly with increasing direct human disturbance. Climate drivers will alter deep-sea biodiversity and associated ecosystem services, and may interact with disturbance from resource extraction activities or even climate geoengineering. We suggest that to ensure the effective management of increasing use of the deep ocean (e.g., for bottom fishing, oil and gas extraction, and deep-seabed mining), environmental management and developing regulations must consider climate change. Strategic planning, impact assessment and monitoring, spatial management, application of the precautionary approach, and full-cost accounting of extraction activities should embrace climate consciousness. Coupled climate and biological modeling approaches applied in the water and on the seafloor can help accomplish this goal. For example, Earth-System Model projections of climate-change parameters at the seafloor reveal heterogeneity in projected climate hazard and time of emergence (beyond natural variability) in regions targeted for deep-seabed mining. Models that combine climate-induced changes in ocean circulation with particle tracking predict altered transport of early life stages (larvae) under climate change. Habitat suitability models can help assess the consequences of altered larval dispersal, predict climate refugia, and identify vulnerable regions for multiple species under climate change. Engaging the deep observing community can support the necessary data provisioning to mainstream climate into the development of environmental management plans. To illustrate this approach, we focus on deep-seabed mining and the International Seabed Authority, whose mandates include regulation of all mineral-related activities in international waters and protecting the marine environment from the harmful effects of mining. However, achieving deep-ocean sustainability under the UN Sustainable Development Goals will require integration of climate consideration across all policy sectors.
The United Arab Emirates (UAE) host valuable coastal and marine biodiversity that is subjected to multiple pressures under extreme conditions. To mitigate impacts on marine ecosystems, the UAE protects almost 12% of its Exclusive Economic Zone. This study mapped and validated the distribution of key coastal and marine habitats, species and critical areas for their life cycle in the Gulf area of the UAE. We identified gaps in the current protection of these ecological features and assessed the quality of the data used. The overall dataset showed good data quality, but deficiencies in information for the coastline of the north-western emirates. The existing protected areas are inadequate to safeguard key ecological features such as mangroves and coastal lagoons. This study offers a solid basis to understand the spatial distribution and protection of marine biodiversity in the UAE. This information should be considered for implementing effective conservation planning and ecosystem-based management.
The threat posed by invasive non-native species worldwide requires a global approach to identify which introduced species are likely to pose an elevated risk of impact to native species and ecosystems. To inform policy, stakeholders and management decisions on global threats to aquatic ecosystems, 195 assessors representing 120 risk assessment areas across all six inhabited continents screened 819 non-native species from 15 groups of aquatic organisms (freshwater, brackish, marine plants and animals) using the Aquatic Species Invasiveness Screening Kit. This multi-lingual decision-support tool for the risk screening of aquatic organisms provides assessors with risk scores for a species under current and future climate change conditions that, following a statistically based calibration, permits the accurate classification of species into high-, medium- and low-risk categories under current and predicted climate conditions. The 1730 screenings undertaken encompassed wide geographical areas (regions, political entities, parts thereof, water bodies, river basins, lake drainage basins, and marine regions), which permitted thresholds to be identified for almost all aquatic organismal groups screened as well as for tropical, temperate and continental climate classes, and for tropical and temperate marine ecoregions. In total, 33 species were identified as posing a 'very high risk' of being or becoming invasive, and the scores of several of these species under current climate increased under future climate conditions, primarily due to their wide thermal tolerances. The risk thresholds determined for taxonomic groups and climate zones provide a basis against which area-specific or climate-based calibrated thresholds may be interpreted. In turn, the risk rankings help decision-makers identify which species require an immediate 'rapid' management action (e.g. eradication, control) to avoid or mitigate adverse impacts, which require a full risk assessment, and which are to be restricted or banned with regard to importation and/or sale as ornamental or aquarium/fishery enhancement.
Studies have shown that food chain length is governed by interactions between species richness, ecosystem size and resource availability. While redundant trophic links may buffer impacts of species loss on food chain length, higher extinction risks associated with predators may result in bottom-heavy food webs with shorter food chains. The lack of consensus in earlier empirical studies relating species richness and food chain length reflects the need to account robustly for the factors described above. In response to this, we conducted an empirical study to elucidate impacts of land-use change on food chain length in tropical forest streams of Southeast Asia. Despite species losses associated with forest loss at our study areas, results from amino acid isotope analyses showed that food chain length was not linked to land use, ecosystem size or resource availability. Correspondingly, species losses did not have a significant effect on occurrence likelihoods of all trophic guilds except herbivores. Impacts of species losses were likely buffered by initial high levels of trophic redundancy, which declined with canopy cover. Declines in trophic redundancy were most drastic amongst invertivorous fishes. Declines in redundancy across trophic guilds were also more pronounced in wider and more resource-rich streams. While our study found limited evidence for immediate land-use impacts on stream food chains, the potential loss of trophic redundancy in the longer term implies increasing vulnerability of streams to future perturbations, as long as land conversion continues unabated.
The rapid expansion of oil palm cultivation in the Neotropics has generated great debate around possible biodiversity impacts. Colombia, for example, is the largest producer of oil palm in the Americas, but the effects of oil palm cultivation on native fauna are poorly understood. Here, we compared how richness, abundance and composition of terrestrial mammal species differ between oil palm plantations and riparian forest in the Colombian Llanos region. Further, we determined the relationships and influence of landscape and habitat level variables on those metrics. We found that species richness and composition differed significantly between riparian forest and oil palm, with site level richness inside oil palm plantations 47% lower, on average, than in riparian forest. Within plantations, mammalian species richness was strongly negatively correlated with cattle abundance, and positively correlated with the density of undergrowth vegetation. Forest structure characteristics appeared to have weak and similar effects on determining mammal species richness and composition along riparian forest strips. Composition at the landscape level was significantly influenced by cover type, percentage of remaining forest and the distance to the nearest town, whereas within oil palm sites, understory vegetation, cattle relative abundance, and canopy cover had significant effects on community composition. Species specific abundance responses varied between land cover types, with oil palm having positive effects on mesopredators, insectivores and grazers. Our findings suggest that increasing habitat complexity, avoiding cattle and retaining native riparian forest-regardless of its structure-inside oil palm-dominated landscapes would help support higher native mammal richness and abundance at both local and landscape scales.
Apex predators can have substantial and complex ecological roles in ecosystems. However, differences in species-specific traits, population densities, and interspecific interactions are likely to determine the strength of apex predators' roles. Here we report complementary studies examining how interactions between predator per capita metabolic rate and population density influenced the biomass, population energy use, and ecological effects of apex predators on their large mammalian prey. We first investigated how large mammal prey resources and field metabolic rates of terrestrial apex predators, comprising large mammals and the Komodo dragon (Varanus komodoensis), influenced their biomass densities and population energy use requirements. We next evaluated whether Komodo dragons, like apex mammalian predators, exerted top-down regulation of their large mammal prey. Comparison of results from field studies demonstrates that Komodo dragons attain mean population biomass densities that are 5.75-231.82 times higher than that of apex mammalian predator species and their guilds in Africa, Asia, and North America. The high biomass of Komodo dragons resulted in 1.96-108.12 times greater population energy use than that of apex mammalian predators. Nevertheless, substantial temporal and spatial variation in Komodo dragon population energy use did not regulate the population growth rates of either of two large mammal prey species, rusa deer (Rusa timorensis) and wild pig (Sus scrofa). We suggest that multiple processes weaken the capacity of Komodo dragons to regulate large mammal prey populations. For example, a low per capita metabolic rate requiring an infrequent and inactive hunting strategy (including scavenging), would minimize lethal and nonlethal impacts on prey populations. We conclude that Komodo dragons differ in their predatory role from, including not being the ecological analogs of, apex mammalian predators.
Primates, like other mammals, exhibit an annual reproductive pattern that ranges from strictly seasonal breeding to giving birth in all months of the year, but factors mediating this variation are not fully understood. We applied both a categorical description and quantitative measures of the birth peak breadth based on daily observations in zoos to characterise reproductive seasonality in 141 primate species with an average of 941 birth events per species. Absolute day length at the beginning of the mating season in seasonally reproducing species was not correlated between populations from natural habitats and zoos. The mid-point of latitudinal range was a major factor associated with reproductive seasonality, indicating a correlation with photoperiod. Gestation length, annual mean temperature, natural diet and Malagasy origin were other important factors associated with reproductive seasonality. Birth seasons were shorter with increasing latitude of geographical origin, corresponding to the decreasing length of the favourable season. Species with longer gestation periods were less seasonal than species with shorter ones, possibly because shorter gestation periods more easily facilitate the synchronisation of reproductive activity with annual cycles. Habitat conditions with higher mean annual temperature were also linked to less-seasonal reproduction, independently of the latitude effect. Species with a high percentage of leaves in their natural diet were generally non-seasonal, potentially because the availability of mature leaves is comparatively independent of seasons. Malagasy primates were more seasonal in their births than species from other regions. This might be due to the low resting metabolism of Malagasy primates, the comparatively high degree of temporal predictability of Malagasy ecosystems, or historical constraints peculiar to Malagasy primates. Latitudinal range showed a weaker but also significant association with reproductive seasonality. Amongst species with seasonal reproduction in their natural habitats, smaller primate species were more likely than larger species to shift to non-seasonal breeding in captivity. The percentage of species that changed their breeding pattern in zoos was higher in primates (30%) than in previous studies on Carnivora and Ruminantia (13 and 10%, respectively), reflecting a higher concentration of primate species in the tropics. When comparing only species that showed seasonal reproduction in natural habitats at absolute latitudes ≤11.75°, primates did not differ significantly from these two other taxa in the proportion of species that changed to a less-seasonal pattern in zoos. However, in this latitude range, natural populations of primates and Carnivora had a significantly higher proportion of seasonally reproducing species than Ruminantia, suggesting that in spite of their generally more flexible diets, both primates and Carnivora are more exposed to resource fluctuation than ruminants.
Plant litter is the major source of energy and nutrients in stream ecosystems and its decomposition is vital for ecosystem nutrient cycling and functioning. Invertebrates are key contributors to instream litter decomposition, yet quantification of their effects and drivers at the global scale remains lacking. Here, we systematically synthesized data comprising 2707 observations from 141 studies of stream litter decomposition to assess the contribution and drivers of invertebrates to the decomposition process across the globe. We found that (1) the presence of invertebrates enhanced instream litter decomposition globally by an average of 74%; (2) initial litter quality and stream water physicochemical properties were equal drivers of invertebrate effects on litter decomposition, while invertebrate effects on litter decomposition were not affected by climatic region, mesh size of coarse-mesh bags or mycorrhizal association of plants providing leaf litter; and (3) the contribution of invertebrates to litter decomposition was greatest during the early stages of litter mass loss (0-20%). Our results, besides quantitatively synthesizing the global pattern of invertebrate contribution to instream litter decomposition, highlight the most significant effects of invertebrates on litter decomposition at early rather than middle or late decomposition stages, providing support for the inclusion of invertebrates in global dynamic models of litter decomposition in streams to explore mechanisms and impacts of terrestrial, aquatic, and atmospheric carbon fluxes.
In the past few years, the research on particle-stabilized emulsion (Pickering emulsion) has mainly focused on the usage of inorganic particles with well-defined shapes, narrow size distributions, and chemical tunability of the surfaces such as silica, alumina, and clay. However, the presence of incompatibility of some inorganic particles that are non-safe to humans and the ecosystem and their poor sustainability has led to a shift towards the development of materials of biological origin. For this reason, nano-dimensional cellulose (nanocellulose) derived from natural plants is suitable for use as a Pickering material for liquid interface stabilization for various non-toxic product formulations (e.g., the food and beverage, cosmetic, personal care, hygiene, pharmaceutical, and biomedical fields). However, the current understanding of nanocellulose-stabilized Pickering emulsion still lacks consistency in terms of the structural, self-assembly, and physio-chemical properties of nanocellulose towards the stabilization between liquid and oil interfaces. Thus, this review aims to provide a comprehensive study of the behavior of nanocellulose-based particles and their ability as a Pickering functionality to stabilize emulsion droplets. Extensive discussion on the characteristics of nanocelluloses, morphology, and preparation methods that can potentially be applied as Pickering emulsifiers in a different range of emulsions is provided. Nanocellulose's surface modification for the purpose of altering its characteristics and provoking multifunctional roles for high-grade non-toxic applications is discussed. Subsequently, the water-oil stabilization mechanism and the criteria for effective emulsion stabilization are summarized in this review. Lastly, we discuss the toxicity profile and risk assessment guidelines for the whole life cycle of nanocellulose from the fresh feedstock to the end-life of the product.
Selective logging that is commonly conducted in tropical forests may change tree species diversity. In rarely disturbed tropical forests, locally rare species exhibit higher survival rates. If this non-random process occurs in a logged forest, the forest will rapidly recover its tree species diversity. Here we determined whether a forest in the Pasoh Forest Reserve, Malaysia, which was selectively logged 40 years ago, recovered its original species diversity (species richness and composition). To explore this, we compared the dynamics of secies diversity between unlogged forest plot (18.6 ha) and logged forest plot (5.4 ha). We found that 40 years are not sufficient to recover species diversity after logging. Unlike unlogged forests, tree deaths and recruitments did not contribute to increased diversity in the selectively logged forests. Our results predict that selectively logged forests require a longer time at least than our observing period (40 years) to regain their diversity.
Zooplankton are major consumers of phytoplankton primary production in marine ecosystems. As such, they represent a critical link for energy and matter transfer between phytoplankton and bacterioplankton to higher trophic levels and play an important role in global biogeochemical cycles. In this Review, we discuss key responses of zooplankton to ocean warming, including shifts in phenology, range, and body size, and assess the implications to the biological carbon pump and interactions with higher trophic levels. Our synthesis highlights key knowledge gaps and geographic gaps in monitoring coverage that need to be urgently addressed. We also discuss an integrated sampling approach that combines traditional and novel techniques to improve zooplankton observation for the benefit of monitoring zooplankton populations and modelling future scenarios under global changes.
Mangrove forests possess multiple functions for the environment and society through their valuable ecosystem services. Along with this, the mangrove forests have large and diverse social values, in combination contributing to the health and wellbeing of the surrounding communities. This study aims (i) to assess the benefits of mangrove forests and their impact on subjective and psychological wellbeing of coastal communities and (ii) to understand the challenges coastal communities face that limit sustainable wellbeing. We have used a mixed methodological approach, combining workshop, interview, and survey, to obtain qualitative and quantitative information from two coastal communities in Malaysia and Indonesia. For quantitative data, 67 participants from both coastal communities participated using a pre-tested structured questionnaire. To obtain opinions from key informants in Malaysia and Indonesia, we organized two stakeholders' workshops and community interviews. When merging these interviews and workshops, we identified the following three themes related to the perception of mangrove forest benefits: (1) the advantage of living in a natural countryside; (2) the natural resources supporting employment, income, and family security; and (3) the increase in subjective and psychological wellbeing. The mean score of wellbeing for Indonesian participants (28.6) was slightly higher than that for Malaysian participants (26.2) and was significant. Overall, the respondents felt happy because the combination of job security and leisure activities supports feeling content and satisfied. The analyses also suggest that the combination of exposure to coastal environments and stress reduction promotes good mental health; however, diagnostic health data are lacking. The lower score of mental wellbeing in Malaysia is attributed to respondents involved in risky fishing activities and local regions with excessive tourism. The findings from this study imply that coastal mangrove forest management plays an important role in the living conditions of coastal communities and their subjective and psychological wellbeing. Hence, restoration and sustainability of mangrove ecosystem are important.
Seaweed (macroalgae) has attracted attention globally given its potential for climate change mitigation. A topical and contentious question is: Can seaweeds' contribution to climate change mitigation be enhanced at globally meaningful scales? Here, we provide an overview of the pressing research needs surrounding the potential role of seaweed in climate change mitigation and current scientific consensus via eight key research challenges. There are four categories where seaweed has been suggested to be used for climate change mitigation: 1) protecting and restoring wild seaweed forests with potential climate change mitigation co-benefits; 2) expanding sustainable nearshore seaweed aquaculture with potential climate change mitigation co-benefits; 3) offsetting industrial CO2 emissions using seaweed products for emission abatement; and 4) sinking seaweed into the deep sea to sequester CO2. Uncertainties remain about quantification of the net impact of carbon export from seaweed restoration and seaweed farming sites on atmospheric CO2. Evidence suggests that nearshore seaweed farming contributes to carbon storage in sediments below farm sites, but how scalable is this process? Products from seaweed aquaculture, such as the livestock methane-reducing seaweed Asparagopsis or low carbon food resources show promise for climate change mitigation, yet the carbon footprint and emission abatement potential remains unquantified for most seaweed products. Similarly, purposely cultivating then sinking seaweed biomass in the open ocean raises ecological concerns and the climate change mitigation potential of this concept is poorly constrained. Improving the tracing of seaweed carbon export to ocean sinks is a critical step in seaweed carbon accounting. Despite carbon accounting uncertainties, seaweed provides many other ecosystem services that justify conservation and restoration and the uptake of seaweed aquaculture will contribute to the United Nations Sustainable Development Goals. However, we caution that verified seaweed carbon accounting and associated sustainability thresholds are needed before large-scale investment into climate change mitigation from seaweed projects.