Data for effects of multiple drivers of environmental change on native and invasive macroalgae in nearshore groundwater dependent ecosystems

Okuhata, B.K., Delevaux, J.M.S., Richards Donà, A., Smith, C.M., Gibson, V.L., Dulai, H., El-Kadi, A.I., Stamoulis, K., Burnett, K.M., Wada, C.A., Bremer, L.L., Effects of multiple drivers of environmental change on native and invasive macroalgae in nearshore groundwater dependent ecosystems

Environmental change scenarios, with a spatial extent of the Keauhou basal aquifer (Hawai‘i), were produced using a recharge coverage from Engott (2011), land use coverages from the State of Hawai‘i (2022) and National Oceanic and Atmospheric Administration (2006); climate change calculations based on Elison Timm et al. (2015), and native forest conversion calculations from Bremer et al. (2021). Scenarios were developed based on the following assumptions:

Scenario 0 (Baseline) assumes current land use, groundwater recharge, and groundwater withdrawal rates (National Oceanic and Atmospheric Administration, 2006; State of Hawai‘i, 2022; Engott, 2011; Commission on Water Resource Management, unpublished data, 2018). Please see Okuhata et al. (2021) for more details regarding the scenario assumptions for the baseline groundwater model.

Scenario 1 (Climate Change) assumes current land use, but with Representative Concentration Pathway (RCP) 8.5 mid-century rainfall projections (Elison Timm et al., 2015), where rainfall and recharge calculations were based on estimates from Giambelluca et al. (2013) and Engott (2011). 

Scenario 2 (Urban Development) assumes RCP 8.5 mid-century rainfall conditions along with future permitted development, which includes an increase in water demand (Fukunaga & Associates, Inc., 2017). 

Scenario 3 (Native Forest Conversion + Urban Development) assumes RCP 8.5 mid-century rainfall conditions and future permitted development, along with the assumption that native forests are not protected and converted to non-native forests (Bremer et al., 2021), therefore altering recharge estimates (Wada et al., 2017; Engott, 2011).

Please note that scenario numbers listed in the groundwater model and marine water quality model shapefiles may differ from the manuscript scenario numbers. The following table assigns the scenario numbers to their respective scenarios in the manuscript, groundwater model, and marine water quality model.

The groundwater model results are in shapefile format and were produced using the program SEAWAT (Langevin et al., 2008). The spatial extent is the Keauhou basal aquifer, and the projection is NAD 1983 UTM Zone 4N. The two polygon shapefiles represent the first and second layers of the groundwater model, and include groundwater level (meters relative to mean sea level), salinity (parts per thousand), temperature (degrees Celsius), nitrogen (milligrams per liter), and phosphorus (milligrams per liter) results under the assumptions of each scenario. The point shapefile represents the simulated discharge at SGD plumes under the assumptions of each scenario.

The marine water quality model results are in floating point TIFF format and were produced using the program R software. The spatial extent is the coastal area of the Keauhou aquifer system, and the geographic coordinate system is WGS 1984. The files include the groundwater discharge (cubic meters per month), salinity (parts per thousand), temperature (degrees Celsius), nitrogen (kilograms per month), and phosphorus (kilograms per month) results under the assumptions of each scenario.

The limu model results are in shapefile format and were produced using the program R software. The spatial extent is the coastal area of the Keauhou aquifer system, and the geographic coordinate system is WGS 1984. The files include the increase and decrease in area (hectares) for Ulva lactuca and Hypnea musciformis under the assumptions of each scenario.

The limu experiment results are derived from a csv file, which reports the Ulva lactuca and Hypnea musciformis measured weights (initial and final) for each growth run. These were used to calculate the weight difference. Included also in the dataset are the fixed and random effects used in the R script to run the model.

Contact Leah Bremer (lbremer@hawaii.edu) or Brytne Okuhata (bokuhata@hawaii.edu) of the University of Hawaiʻi for more information on these files.