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Keystone species have large ecological effects relative to their abundance and have been identified in many ecosystems. However, global change is pervasively altering environmental conditions, potentially elevating new species to keystone roles. Here, we reveal that a historically innocuous grazer—the marsh crab Sesarma reticulatum —is rapidly reshaping the geomorphic evolution and ecological organization of southeastern US salt marshes now burdened by rising sea levels. Our analyses indicate that sea-level rise in recent decades has widely outpaced marsh vertical accretion, increasing tidal submergence of marsh surfaces, particularly where creeks exhibit morphologies that are unable to efficiently drain adjacent marsh platforms. In these increasingly submerged areas, cordgrass decreases belowground root:rhizome ratios, causing substrate hardness to decrease to within the optimal range for Sesarma burrowing. Together, these bio-physical changes provoke Sesarma to aggregate in high-density grazing and burrowing fronts at the heads of tidal creeks (hereafter, creekheads). Aerial-image analyses reveal that resulting “ Sesarma- grazed” creekheads increased in prevalence from 10 ± 2% to 29 ± 5% over the past <25 y and, by tripling creek-incision rates relative to nongrazed creekheads, have increased marsh-landscape drainage density by 8 to 35% across the region. Field experiments further demonstrate that Sesarma- grazed creekheads, through their removal of vegetation that otherwise obstructs predator access, enhance the vulnerability of macrobenthic invertebrates to predation and strongly reduce secondary production across adjacent marsh platforms. Thus, sea-level rise is creating conditions within which Sesarma functions as a keystone species that is driving dynamic, landscape-scale changes in salt-marsh geomorphic evolution, spatial organization, and species interactions. 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.