@article {fagherazzi_salt_2020,
	title = {Salt {Marsh} {Dynamics} in a {Period} of {Accelerated} {Sea} {Level} {Rise}},
	journal = {Journal of Geophysical Research: Earth Surface},
	volume = {125},
	number = {8},
	year = {2020},
	month = {aug},
	issn = {2169-9003, 2169-9011},
	doi = {10.1029/2019JF005200},
	url = {https://onlinelibrary.wiley.com/doi/10.1029/2019JF005200},
	author = {Fagherazzi, Sergio and Mariotti, Giulio and Leonardi, Nicoletta and Canestrelli, Alberto and Nardin, William and Kearney, William S.}
}
@article {kearney_sea-level_2019,
	title = {Sea-level rise and storm surges structure coastal forests into persistence and regeneration niches},
	journal = {PLOS ONE},
	volume = {14},
	number = {5},
	year = {2019},
	month = {may},
	pages = {e0215977},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0215977},
	url = {https://dx.plos.org/10.1371/journal.pone.0215977},
	author = {Kearney, William S. and Fernandes, Arnold and Fagherazzi, Sergio},
	editor = {Magar, Vanesa}
}
@article {fernandes_declining_2018,
	title = {Declining Radial Growth Response of Coastal Forests to Hurricanes and Nor{\textquoteright}easters},
	journal = {Journal of Geophysical Research: Biogeosciences},
	volume = {123},
	year = {2018},
	pages = {832{\textendash}849},
	abstract = {The Mid-Atlantic coastal forests in Virginia are stressed by episodic disturbance from hurricanes and nor{\textquoteright}easters. Using annual tree ring data, we adopt a dendroclimatic and statistical modeling approach to understand the response and resilience of a coastal pine forest to extreme storm events, over the past few decades. Results indicate that radial growth of trees in the study area is influenced by age, regional climate trends, and individual tree effects but dominated periodically by growth disturbance due to storms. We evaluated seven local extreme storm events to understand the effect of nor{\textquoteright}easters and hurricanes on radial growth. A general decline in radial growth was observed in the year of the extreme storm and 3 years following it, after which the radial growth started recovering. The decline in radial growth showed a statistically significant correlation with the magnitude of the extreme storm (storm surge height and wind speed). This study contributes to understanding declining tree growth response and resilience of coastal forests to past disturbances. Given the potential increase in hurricanes and storm surge severity in the region, this can help predict vegetation response patterns to similar disturbances in the future.},
	keywords = {coastal vegetation, floods, LTER, storm surge, tree ring},
	issn = {2169-8961},
	doi = {10.1002/2017JG004125},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/2017JG004125},
	author = {Fernandes, Arnold and Rollinson, Christine R. and Kearney, William S. and Dietze, Michael C. and Fagherazzi, Sergio}
}
@article {kearney_stage-discharge_2017,
	title = {Stage-discharge relationship in tidal channels},
	journal = {Limnology and Oceanography: Methods},
	volume = {15},
	year = {2017},
	pages = {394{\textendash}407},
	abstract = {Long-term records of the flow of water through tidal channels are essential to constrain the budgets of sediments and biogeochemical compounds in salt marshes. Statistical models which relate discharge to water level allow the estimation of such records from more easily obtained records of water stage in the channel. Here, we compare four different types of stage-discharge models, each of which captures different characteristics of the stage-discharge relationship. We estimate and validate each of these models on a 2-month long time series of stage and discharge obtained with an acoustic Doppler current profiler in a salt marsh channel. We find that the best performance is obtained by models that account for the nonlinear and time-varying nature of the stage-discharge relationship. Good performance can also be obtained from a simplified version of these models, which captures nonlinearity and nonstationarity without the complexity of the fully nonlinear or time-varying models.},
	issn = {1541-5856},
	doi = {10.1002/lom3.10168},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/lom3.10168},
	author = {Kearney, William S. and Mariotti, Giulio and Deegan, Linda A. and Fagherazzi, Sergio}
}
