4.1 Article Data Paper

Groundwater, soil moisture, light and weather data collected in a coastal forest bordering a salt marsh in the Delmarva Peninsula (VA)

Journal

DATA IN BRIEF
Volume 45, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.dib.2022.108584

Keywords

Forest hydrology; Coastal hydrology; Conductivity; Water content; External inputs

Funding

  1. USA National Science Foundation [1832221, 2012322]
  2. Division Of Earth Sciences
  3. Directorate For Geosciences [2012322] Funding Source: National Science Foundation

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The data presented in this paper were collected at eight sites in a coastal forest in the Delmarva Peninsula, VA USA, representing the progressive forest retreat and marsh expansion driven by sea level rise. The study focused on measuring groundwater level, electrical conductivity, soil water content, and collecting weather and light data to understand the effects of hydrological variables on local ecology. The data collected are crucial for estimating the feedback between hydrology and ecology and quantifying forest retreat due to flooding and salinization.
Data presented in this paper were collected in eight sites across a coastal forest in the Delmarva Peninsula, VA USA. The sites, located along transects from the marshland to the inner forest, are representative of the progressive forest retreat and the consequent marsh expansion driven by sea level rise. The sites are divided in marsh, transition zone where marsh vegetation is invading the forest, low forest, where tree dieback is widespread, intermediate forest (medium forest), where trees show signs of stress, and high forest, where trees are healthy. Sea level rise and storm surge events are the drivers of the forest conversion to salt marsh. Groundwater level and electrical conductivity were measured in a well at each site. Soil water content and electrical conductivity data were measured in the first 7-cm layer of soil. Weather and light data were collected to determine the effects of external inputs on groundwater and soil moisture datasets and to relate hydrological variables and illuminance to local ecology. Data collected are fundamental to estimate feedbacks between hydrology and ecology in the study area and to quantify forest retreat due to flooding and salinization. (c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

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