What new word or phrase would you add to the dictionary to help scientists explain the events of 2020 to future generations?To submit, go to www.sciencemag.org/nextgen-voices Deadline for submissions is 20 November. A selection of the best responses will be published in the 1 January 2021 issue of Science. Anonymous submissions will not be considered.
Vegetation patterns during salt marsh restoration reflect underlying processes related to colonization, reproduction, and interactions of halotolerant plants. Examining both pattern and process during recovery is valuable for understanding and managing salt marsh restoration projects. We present a decade of vegetation dynamics during salt marsh restoration (2011–2020) at a study site in the Bay of Fundy with megatidal amplitudes, strong currents, cold winter temperatures, and ice. We mainly investigated reproduction (asexual and sexual) and associated spread rates of Spartina grasses, and their health-related states (stem density, canopy height, and percent flowering) which help inform the probability of processes occurring. We also estimated modes of colonization and began quantifying the effects of interspecific interactions and environmental conditions on plant state. Spartina pectinata was the only pastureland plant to survive dike-breaching and saltwater intrusion in 2010; however, it was stunted compared to reference plants. Spartina pectinata patches remained consistent initially, before decreasing in size, and disappearing by the fifth year (2015). This early dynamic may provide initial protection to a developing salt marsh before Spartina alterniflora becomes established. Spartina alterniflora first colonized the sites in year 2 (2012), likely via deposition of rhizomal material, and then spread asexually before seedlings (sexual reproduction) appeared in year 4 (2014). Vegetation cover subsequently increased greatly until near-complete in year 9 (2019). The early successional dynamics of S. pectinata and S. alterniflora occurred spatially independently of each other, and likely contributed to sediment retention, creating an improved environment for S. patens, the dominant high marsh species in our region. Spartina patens have been slowly spreading into restoration sites from high elevation areas since year 6 (2016). We expect that competition between S. alterniflora and S. patens will result in the typical distinct zonation between high and low marsh zones. A next study will use the quantified processes for spatial-explicit modeling to simulate patterns of vegetation recovery, and to evaluate different salt marsh restoration strategies for the Bay of Fundy and elsewhere. Thus, proper identification and quantification of pattern-building processes in salt marsh vegetation recovery, the focus of our present study, was an essential step.
Abstract. Salt marshes are intertidal ecosystems valuable for services including coastal protection and carbon sequestration. Restoration of salt marshes is popular in this era of climate change and sea-level rise, especially in areas where marshes have been historically altered, including in the Bay of Fundy. Salt marsh restoration involves landcover change through time as a community of halophytic vegetation develops in the study area. Restoration sites are difficult to survey using traditional on-foot methods, and developing remote sensing methods to survey them would increase efficiency of monitoring. The purpose of our study was to assess the capability of UAV multispectral imagery to map landcovers in a salt marsh restoration site in the Musquash Estuary, New Brunswick, Canada. We used the Random Forests (RF) supervised classifier and validated our maps using field data. We also evaluated the importance of textural features by running two classifications, with and without textural features. The classification omitting textural features had lower classification and validation accuracies (96.29 % and 91.23 %, respectively) than the classification and validation accuracies obtained by including textural features (99.56 % and 96.84 %, respectively). Additional work is required to test our method in different locations and seasons.
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