Beyond just sea-level rise: considering macroclimatic drivers within coastal wetland vulnerability assessments to climate change

Due to their position at the land-sea interface, coastal wetlands are vulnerable to many aspects of climate change. However, climate change vulnerability assessments for coastal wetlands generally focus solely on sea-level rise without considering the effects of other facets of climate change. Across the globe and in all ecosystems, macroclimatic drivers (e.g., temperature and rainfall regimes) greatly influence ecosystem structure and function. Macroclimatic drivers have been the focus of climate change-related threat evaluations for terrestrial ecosystems, but largely ignored for coastal wetlands. In some coastal wetlands, changing macroclimatic conditions are expected to result in foundation plant species replacement, which would affect the supply of certain ecosystem goods and services and could affect ecosystem resilience. As examples, we highlight several ecological transition zones where small changes in macroclimatic conditions would result in comparatively large changes in coastal wetland ecosystem structure and function. Our intent in this communication is not to minimize the importance of sea-level rise. Rather, our overarching aim is to illustrate the need to also consider macroclimatic drivers within vulnerability assessments for coastal wetlands

Integrating Remote Sensing with Ground-based Observations to Quantify the Effects of an Extreme Freeze Event on Black Mangroves (Avicennia germinans) at the Landscape Scale

Climate change is altering the frequency and intensity of extreme weather events. Quantifying ecosystem responses to extreme events at the landscape scale is critical for understanding and responding to climate-driven change but is constrained by limited data availability. Here, we integrated remote sensing with ground-based observations to quantify landscape-scale vegetation damage from an extreme climatic event. We used ground- and satellite-based black mangrove (Avicennia germinans) leaf damage data from the northern Gulf of Mexico (USA and Mexico) to examine the effects of an extreme freeze in a region where black mangroves are expanding their range. The February 2021 event produced coastal temperatures as low as − 10 °C in some areas, exceeding thresholds for A. germinans damage and mortality. We used Sentinel-2 surface reflectance data to assess vegetation greenness before and after the freeze, along with ground-based observations of A. germinans leaf damage. Our results show a negative, nonlinear threshold relationship between A. germinans leaf damage and minimum temperature, with a temperature threshold for leaf damage near − 6 °C. Satellite-based analyses indicate that, at the landscape scale, damage was particularly severe along the central Texas coast, where the freeze event affected \u3e 2000 ha of A. germinans-dominated coastal wetlands. Our analyses highlight the value of pairing remotely sensed data with regional, ground-based observations for quantifying and extrapolating the effects of extreme freeze events on mangroves and other tropical, cold-sensitive plants. The results also demonstrate how extreme freeze events govern the expansion and contraction of mangroves near northern range limits in North America

Rapidly Changing Range Limits in a Warming World: Critical Data Limitations and Knowledge Gaps for Advancing Understanding of Mangrove Range Dynamics in the Southeastern USA

Climate change is altering species’ range limits and transforming ecosystems. For example, warming temperatures are leading to the range expansion of tropical, cold-sensitive species at the expense of their cold-tolerant counterparts. In some temperate and subtropical coastal wetlands, warming winters are enabling mangrove forest encroachment into salt marsh, which is a major regime shift that has significant ecological and societal ramifications. Here, we synthesized existing data and expert knowledge to assess the distribution of mangroves near rapidly changing range limits in the southeastern USA. We used expert elicitation to identify data limitations and highlight knowledge gaps for advancing understanding of past, current, and future range dynamics. Mangroves near poleward range limits are often shorter, wider, and more shrublike compared to their tropical counterparts that grow as tall forests in freeze-free, resource-rich environments. The northern range limits of mangroves in the southeastern USA are particularly dynamic and climate sensitive due to abundance of suitable coastal wetland habitat and the exposure of mangroves to winter temperature extremes that are much colder than comparable range limits on other continents. Thus, there is need for methodological refinements and improved spatiotemporal data regarding changes in mangrove structure and abundance near northern range limits in the southeastern USA. Advancing understanding of rapidly changing range limits is critical for foundation plant species such as mangroves, as it provides a basis for anticipating and preparing for the cascading effects of climate-induced species redistribution on ecosystems and the human communities that depend on their ecosystem services

Climate and plant controls on soil organic matter in coastal wetlands

Coastal wetlands are among the most productive and carbon‐rich ecosystems on Earth. Long‐term carbon storage in coastal wetlands occurs primarily belowground as soil organic matter (SOM). In addition to serving as a carbon sink, SOM influences wetland ecosystem structure, function, and stability. To anticipate and mitigate the effects of climate change, there is a need to advance understanding of environmental controls on wetland SOM. Here, we investigated the influence of four soil formation factors: climate, biota, parent materials, and topography. Along the northern Gulf of Mexico, we collected wetland plant and soil data across elevation and zonation gradients within 10 estuaries that span broad temperature and precipitation gradients. Our results highlight the importance of climate–plant controls and indicate that the influence of elevation is scale and location dependent. Coastal wetland plants are sensitive to climate change; small changes in temperature or precipitation can transform coastal wetland plant communities. Across the region, SOM was greatest in mangrove forests and in salt marshes dominated by graminoid plants. SOM was lower in salt flats that lacked vascular plants and in salt marshes dominated by succulent plants. We quantified strong relationships between precipitation, salinity, plant productivity, and SOM. Low precipitation leads to high salinity, which limits plant productivity and appears to constrain SOM accumulation. Our analyses use data from the Gulf of Mexico, but our results can be related to coastal wetlands across the globe and provide a foundation for predicting the ecological effects of future reductions in precipitation and freshwater availability. Coastal wetlands provide many ecosystem services that are SOM dependent and highly vulnerable to climate change. Collectively, our results indicate that future changes in SOM and plant productivity, regulated by cascading effects of precipitation on freshwater availability and salinity, could impact wetland stability and affect the supply of some wetland ecosystem services

Linear and nonlinear effects of temperature and precipitation on ecosystem properties in tidal saline wetlands

Climate greatly influences the structure and functioning of tidal saline wetland ecosystems. However, there is a need to better quantify the effects of climatic drivers on ecosystem properties, particularly near climate-sensitive ecological transition zones. Here, we used climate- and literature-derived ecological data from tidal saline wetlands to test hypotheses regarding the influence of climatic drivers (i.e., temperature and precipitation regimes) on the following six ecosystem properties: canopy height, biomass, productivity, decomposition, soil carbon density, and soil carbon accumulation. Our analyses quantify and elucidate linear and nonlinear effects of climatic drivers. We quantified positive linear relationships between temperature and above-ground productivity and strong positive nonlinear (sigmoidal) relationships between (1) temperature and above-ground biomass and canopy height and (2) precipitation and canopy height. Near temperature-controlled mangrove range limits, small changes in temperature are expected to trigger comparatively large changes in biomass and canopy height, as mangrove forests grow, expand, and, in some cases, replace salt marshes. However, within these same transition zones, temperature- induced changes in productivity are expected to be comparatively small. Interestingly, despite the significant above-ground height, biomass, and productivity relationships across the tropical–temperate mangrove–marsh transition zone, the relationships between temperature and soil carbon density or soil carbon accumulation were not significant. Our literature review identifies several ecosystem properties and many regions of the world for which there are insufficient data to fully evaluate the influence of climatic drivers, and the identified data gaps can be used by scientists to guide future research. Our analyses indicate that near precipitation-controlled transition zones, small changes in precipitation are expected to trigger comparatively large changes in canopy height. However, there are scant data to evaluate the influence of precipitation on other ecosystem properties. There is a need for more decomposition data across climatic gradients, and to advance understanding of the influence of changes in precipitation and freshwater availability, additional ecological data are needed from tidal saline wetlands in arid climates. Collectively, our results can help scientists and managers better anticipate the linear and nonlinear ecological consequences of climate change for coastal wetlands

Rapidly Changing Range Limits in a Warming World: Critical Data Limitations and Knowledge Gaps for Advancing Understanding of Mangrove Range Dynamics in the Southeastern USA

Climate change is altering species’ range limits and transforming ecosystems. For example, warming temperatures are leading to the range expansion of tropical, cold-sensitive species at the expense of their cold-tolerant counterparts. In some temperate and subtropical coastal wetlands, warming winters are enabling mangrove forest encroachment into salt marsh, which is a major regime shift that has significant ecological and societal ramifications. Here, we synthesized existing data and expert knowledge to assess the distribution of mangroves near rapidly changing range limits in the southeastern USA. We used expert elicitation to identify data limitations and highlight knowledge gaps for advancing understanding of past, current, and future range dynamics. Mangroves near poleward range limits are often shorter, wider, and more shrublike compared to their tropical counterparts that grow as tall forests in freeze-free, resource-rich environments. The northern range limits of mangroves in the southeastern USA are particularly dynamic and climate sensitive due to abundance of suitable coastal wetland habitat and the exposure of mangroves to winter temperature extremes that are much colder than comparable range limits on other continents. Thus, there is need for methodological refinements and improved spatiotemporal data regarding changes in mangrove structure and abundance near northern range limits in the southeastern USA. Advancing understanding of rapidly changing range limits is critical for foundation plant species such as mangroves, as it provides a basis for anticipating and preparing for the cascading effects of climate-induced species redistribution on ecosystems and the human communities that depend on their ecosystem services

Lacunarity As a Tool For Assessing Landscape Configuration Over Time and Informing Long-Term Monitoring: An Example Using Seagrass

Context: Seagrasses are submerged marine plants that have been declining globally at increasing rates. Natural resource managers rely on monitoring programs to detect and understand changes in these ecosystems. Technological advancements are allowing for the development of patch-level seagrass maps, which can be used to explore seagrass meadow spatial patterns. Objectives: Our research questions involved comparing lacunarity, a measure of landscape configuration, for seagrass to assess cross-site differences in areal coverage and spatial patterns through time. We also discussed how lacunarity could help natural resource managers with monitoring program development and restoration decisions and evaluation. Methods: We assessed lacunarity of seagrass meadows for various box sizes (0.0001 ha to 400.4 ha) around Cat Island and Ship Island, Mississippi (USA). For Cat Island, we used seagrass data from 2011 to 2014. For Ship Island, we used seagrass data for seven dates between 1963 and 2014. Results: Cat Island, which had more continuous seagrass meadows, had lower lacunarity (i.e., denser coverage) compared to Ship Island, which had patchier seagrass beds. For Ship Island, we found a signal of disturbance and path toward recovery from Hurricane Camille in 1969. Finally, we highlighted how lacunarity curves could be used as one of multiple considerations for designing monitoring programs, which are commonly used for seagrass monitoring. Conclusions: Lacunarity can help quantify spatial pattern dynamics, but more importantly, it can assist with natural resource management by defining fragmentation and potential scales for monitoring. This approach could be applied to other environments, especially other coastal ecosystems

A 1.2 Billion Pixel Human-Labeled Dataset for Data-Driven Classification of Coastal Environments

Abstract The world’s coastlines are spatially highly variable, coupled-human-natural systems that comprise a nested hierarchy of component landforms, ecosystems, and human interventions, each interacting over a range of space and time scales. Understanding and predicting coastline dynamics necessitates frequent observation from imaging sensors on remote sensing platforms. Machine Learning models that carry out supervised (i.e., human-guided) pixel-based classification, or image segmentation, have transformative applications in spatio-temporal mapping of dynamic environments, including transient coastal landforms, sediments, habitats, waterbodies, and water flows. However, these models require large and well-documented training and testing datasets consisting of labeled imagery. We describe “Coast Train,” a multi-labeler dataset of orthomosaic and satellite images of coastal environments and corresponding labels. These data include imagery that are diverse in space and time, and contain 1.2 billion labeled pixels, representing over 3.6 million hectares. We use a human-in-the-loop tool especially designed for rapid and reproducible Earth surface image segmentation. Our approach permits image labeling by multiple labelers, in turn enabling quantification of pixel-level agreement over individual and collections of images

The Impact of Lidar Elevation Uncertainty on Mapping Intertidal Habitats on Barrier Islands

While airborne lidar data have revolutionized the spatial resolution that elevations can be realized, data limitations are often magnified in coastal settings. Researchers have found that airborne lidar can have a vertical error as high as 60 cm in densely vegetated intertidal areas. The uncertainty of digital elevation models is often left unaddressed; however, in low-relief environments, such as barrier islands, centimeter differences in elevation can affect exposure to physically demanding abiotic conditions, which greatly influence ecosystem structure and function. In this study, we used airborne lidar elevation data, in situ elevation observations, lidar metadata, and tide gauge information to delineate low-lying lands and the intertidal wetlands on Dauphin Island, a barrier island along the coast of Alabama, USA. We compared three different elevation error treatments, which included leaving error untreated and treatments that used Monte Carlo simulations to incorporate elevation vertical uncertainty using general information from lidar metadata and site-specific Real-Time Kinematic Global Position System data, respectively. To aid researchers in instances where limited information is available for error propagation, we conducted a sensitivity test to assess the effect of minor changes to error and bias. Treatment of error with site-specific observations produced the fewest omission errors, although the treatment using the lidar metadata had the most well-balanced results. The percent coverage of intertidal wetlands was increased by up to 80% when treating the vertical error of the digital elevation models. Based on the results from the sensitivity analysis, it could be reasonable to use error and positive bias values from literature for similar environments, conditions, and lidar acquisition characteristics in the event that collection of site-specific data is not feasible and information in the lidar metadata is insufficient. The methodology presented in this study should increase efficiency and enhance results for habitat mapping and analyses in dynamic, low-relief coastal environments

Radar and optical mapping of surge persistence and marsh dieback along the New Jersey Mid-Atlantic coast after Hurricane Sandy

<p>This study combined a radar-based time series of Hurricane Sandy surge and estimated persistence with optical sensor-based marsh condition change to assess potential causal linkages of surge persistence and marsh condition change along the New Jersey Atlantic Ocean coast. Results based on processed TerraSAR-X and COSMO-SkyMed synthetic aperture radar (SAR) images indicated that surge flooding persisted for 12 h past landfall in marshes from Great Bay to Great Egg Harbor Bay and up to 59 h after landfall in many back-barrier lagoon marshes. Marsh condition change (i.e. loss of green marsh vegetation) was assessed from optical satellite images (Satellite Pour l’Observation de la Terre and Moderate Resolution Imaging Spectroradiometer) collected before and after Hurricane Sandy. High change in condition often showed spatial correspondence, with high surge persistence in marsh surrounding the lagoon portion of Great Bay, while in contrast, low change and high persistence spatial correspondence dominated the interior marshes of the Great Bay and Great Egg Harbor Bay estuaries. Salinity measurements suggest that these areas were influenced by freshwater discharges after landfall possibly mitigating damage. Back-barrier marshes outside these regions exhibited mixed correspondences. In some cases, topographic features supporting longer surge persistence suggested that non-correspondence between radar and optical data-based results may be due to differential resilience; however, in many cases, reference information was lacking to determine a reason for non-correspondence.</p