DOI: 10.5061/dryad.hhmgqnkjn
title: Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use

description: Changes in climate and land-use and land-cover (LULC) are expected to
 influence surface water runoff and nutrient characteristics of estuarine
 watersheds, but the extent to which estuaries are vulnerable to altered
 nutrient loading under future conditions is poorly understood. The present
 work aims to address this gap through the development of a new
 vulnerability assessment framework that accounts for (1) estuarine
 exposure to projected changes in total nitrogen (TN) and total phosphorus
 (TP) loads as a function of LULC and climate change under several
 scenarios to altered nutrient loads, (2) sensitivity (i.e., how
 responsive estuaries are to altered nutrient loads), and (3)
 adaptive capacity (i.e., how the socio-ecological system can use existing
 resources to reduce the impacts associated with increased exposure). The
 framework was applied to 112 estuaries and their contributing watersheds
 across the contiguous U.S., specifically to look at regional variability
 in estuarine vulnerability to nutrient loading. Study findings
 revealed that the largest increases in estuarine nutrient loads are
 expected in the North and South Atlantic regions and eastern Gulf of
 Mexico, while the lowest increase is expected in the North and South
 Pacific regions and the western Gulf of Mexico. However, the North
 Atlantic and the South Pacific had the highest adaptive capacity, which
 could potentially counteract the effects of LULC and climate change on
 nutrient loads. Our findings illustrate the benefits of integrating
 natural and socio-ecological factors to identify opportunities to develop
 adaptation plans and policies to mitigate ecological degradation in
 vitally important estuaries. A web-based application has
 been developed to visualize and download the data.
description: <strong>The vulnerability framework</strong> is
 composed of three key components: the  exposure (i.e., magnitude and
 extent of exposure to change-driven impacts), sensitivity (i.e.,  how a
 system is affected by exposure to hazards), and adaptive capacity (i.e.,
 potential ability and opportunities to adapt or accommodate the combined
 effects of the exposure and sensitivity of the system). The dataset gives
 the score for the indicators used in the exposure, sensitivity, and
 adaptive capacity.
 <strong>Exposure</strong> is defined as the degree to
 which an estuarine system is projected to be exposed to increased nutrient
 loading through terrestrial surface water runoff, altered by changes in
 precipitation and LULC. To compute the exposure,  average changes in TN
 and TP loads between the historical (1990-2020) and future (2035-2065)
 periods obtained from STEPLgrid (Montefiore and Nelson, 2022) were
 calculated annually (∆<sub>TN</sub> and
 ∆<sub>TP</sub>). ∆<sub>TN</sub> and
 ∆<sub>TP</sub> were re-scaled from 0 to 1 for each nutrient
 using a linear relationship, where 0 represented estuarine watersheds with
 negative change (i.e., decreased nutrient loading under future climate and
 LULC scenarios) and 1 equated to watersheds with a positive change in
 nutrient loads equal to or greater than 200%. Exposure scores were
 computed for 8 climate (i.e., RCPs 4.5. and 8.5) and land-use scenarios
 (i.e., A1B, A2, B1, B2) combinations for TN and TP. 
 <strong>Sensitivity</strong> was evaluated using two
 indicators: the degree to which a system is (1) already eutrophic, and (2)
 physical susceptible to increased nutrient loading. The column
 "eutrophication" reports the eutrophic conditions of the
 estuaries.  The columns susceptibility_TN and susceptibility_TP represent
 the physical susceptibility of the estuaries to TN and TP loads, which
 were re-scaled from 0 to 1 (i.e., lowest to highest susceptibility of
 estuaries to nutrient loads).  <strong>Adaptive
 capacity</strong> is defined as the magnitude of existing
 socio-ecological resources available to an estuarine system to cope with,
 adapt to, or mitigate changes in nutrient loads. The adaptive capacity was
 composed of the <strong>(1) human adaptive
 capacity </strong>and <strong>(2) natural adaptive
 capacity</strong>. The human and natural adaptive capacity
 categories were represented by scores ranging from 0 to 1, with 0 given to
 estuarine watersheds with low adaptive capacity (i.e., low ability to
 mitigate nutrient loading impact) and 1 to those with high adaptive
 capacity (i.e., high ability to mitigate nutrient loading
 impact). <em>The human adaptive
 capacity</em> category was composed of two indicators: access to
 scientific knowledge and legislative/governmental actions already
 undertaken.Access to scientific knowledge was composed of three
 sub-indicators: (1) the number of published peer-reviewed research
 articles related to climate change, nutrients, and eutrophication of the
 estuary, (2) the number of academic staff in R1 and R2 universities in the
 states where the watershed was located, normalized by the state
 population, and (3) the information provided by the long-term monitoring
 stations present within the estuary and its watershed. The
 legislative/governmental actions already undertaken was composed of three
 sub-indicators (1) the existence of a climate adaptation plan, (2) the
 amount of the annual state budget dedicated to environmental and natural
 resources departments normalized by the population of the respective
 state, and (3) the state adoption of numeric water quality parameter
 criteria. Each sub-indicator was re-scaled from 0 to 1 and an overall
 score of the human adaptive capacity category was calculated by averaging
 the scores of the two sub-indicators. <em>The
 natural adaptive capacity</em> indicator was calculated as the
 density of wetlands per estuarine watershed. Note that the human and
 natural adaptive capacity scores were not combined and should not
 be. The vulnerability data can also be
 accessed and visualized through the web-based application.
description: The tabular files
 can be opened with Excel. The shapefiles can be opened with any
 GIS software (e.g., QGIS, ArcGIS, R, Python).