The data described here is the Main Hawaiian Islands (MHI) Atlantis Ecosystem model output data for biomass and catch trends of various functional groups under different scenarios. Hind-cast simulations were run for model validation, and forecast simulations were run for ecological forecasting under different climate change scenarios. The data used in the model comes from benthic and coral reef fish surveys conducted by Pacific Island Fisheries Science Center (PIFSC) RAMP cruises, recreational fishery data from MRIP, commercial fishery data administered by WPacFIN, bottomfish fishery-dependent and independent data from PIFSC, and sea turtle and monk seal data from the PIFSC. Model simulations of ecological forecasting were carried out and included 50 year forecast (2020-2070) simulations with and without the predicted effects of climate change (ocean warming and ocean acidification) evaluating changes in ecological and social state components. The MHI Atlantis Ecosystem Model incorporates the coral-specific modules that were developed for the Guam Atlantis model. The model can be used for management-strategy evaluation by simulating existing and alternative fisheries and land-use regulations and comparing the results under different management and environmental change scenarios (e.g., in terms of fish biomass, coral cover, fisherman participation).

Coral reefs provide a wide range of ecosystem services that are valued differently by different users. Managers are challenged to comprehensively address the full suite of pressures that act simultaneously on these ecosystem state variables and dynamics. We developed a decision-support tool using an ecosystem model, Ecopath with Ecosim, that ranks the efficiency of potential management strategies in evaluating ecological and socio-economic trade-offs based on multiple indicators for coral reef ecosystem services in Puako, Hawaii Island. Our results indicate that current management is inadequate to prevent further declines in coral reef resources and that improved fishery management can mitigate the detrimental effects of expected bleaching-related coral mortalities on the ecosystem services in the next 15 years. The scenario that minimized conflicts between stakeholders was "Only Line Fishing" and to a lesser extent a reduction in fishing effort. Results include the biomass (tons per square kilometer) for several groups of marine organisms (invertivores, coralivores, planktivores, browsers, grazers, sharks, reef fishes, sea turtles, invertebrates, corals, algae, and plankton) for 2017 and 2032 under the current and alternative management scenarios and the relative performance of the indicators under six management scenarios in 2032 and compared to current management. The data are available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.4sh45

The files described here are the Main Hawaiian Islands (MHI) Atlantis Ecosystem model input files used in for testing CMIP6 climate scenarios developed by main Hawaiian Islands ROMS. These input files were used to run forecast simulations under three different CMIP6 climate change scenarios: low-emission (SSP1-2.6), moderate-emission (SSP2-4.5), and high-emission (SSP3-7.0). Files included are parameter (.prm), initial conditions (.nc), and land-based source pollutants (LBSP) forcing files. The parameter files include a run file, biological parameters, forcing parameters (list climate and pollution forcing files), harvest parameters (fishing mortality), and physics parameters. The LBSP forcing files are time series files representing spatial deposition of nutrients and sediments from land to the nearshore regions covered by Hawaii Atlantis. In recalibrating the current model based on updated climate forcing files (ROMS projections), the parameter and initial conditions files have been adjusted since initial model development. The ROMS projections used to force Hawaii Atlantis are not included in this data set, as they are from a different project. Hawaii Atlantis was initially developed at PIFSC and further details regarding the model, as well as outputs of a model run based on older inputs, are hosted as InPort catalog item 55245. The LBSP forcing files hosted here were developed based on Ocean Tipping Points project data as part of initial model development.

The files described here are the Main Hawaiian Islands (MHI) Atlantis Ecosystem model input files used in for testing CMIP6 climate scenarios developed by main Hawaiian Islands ROMS. These input files were used to run forecast simulations under three different CMIP6 climate change scenarios: low-emission (SSP1-2.6), moderate-emission (SSP2-4.5), and high-emission (SSP3-7.0). Files included are parameter (.prm), initial conditions (.nc), and land-based source pollutants (LBSP) forcing files. The parameter files include a run file, biological parameters, forcing parameters (list climate and pollution forcing files), harvest parameters (fishing mortality), and physics parameters. The LBSP forcing files are time series files representing spatial deposition of nutrients and sediments from land to the nearshore regions covered by Hawaii Atlantis. In recalibrating the current model based on updated climate forcing files (ROMS projections), the parameter and initial conditions files have been adjusted since initial model development. The ROMS projections used to force Hawaii Atlantis are not included in this data set, as they are from a different project. Hawaii Atlantis was initially developed at PIFSC and further details regarding the model, as well as outputs of a model run based on older inputs, are hosted as InPort catalog item 55245. The LBSP forcing files hosted here were developed based on Ocean Tipping Points project data as part of initial model development.

We integrated recent climate model projections developed for the State of Hawai’i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (Tmin, Tmean, Tmax) and mean precipitation (Pmean) data at 250 m resolution. We used observation-based data for the baseline bioclimatic variables from the Rainfall Atlas of Hawai’i. We used the most up-to-date dynamically downscaled future projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two projections into a suite of 19 bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions specifically for the Hawaiian Islands. These bioclimatic variables are available state-wide for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under RCP 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections). As Hawai’i is characterized by two 6-month seasons, we also provide mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate.

We integrated recent climate model projections developed for the State of Hawai’i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (Tmin, Tmean, Tmax) and mean precipitation (Pmean) data at 250 m resolution. We used observation-based data for the baseline bioclimatic variables from the Rainfall Atlas of Hawai’i. We used the most up-to-date dynamically downscaled future projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two projections into a suite of 19 bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions specifically for the Hawaiian Islands. These bioclimatic variables are available state-wide for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under RCP 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections). As Hawai’i is characterized by two 6-month seasons, we also provide mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate.

The goal of this project was to produce estimates of the change in three ecosystem services - water yield, sediment runoff, and reef productivity (or seafood benefits) - under climate change and three newly developed land cover scenarios. The developed land cover scenarios expanded upon the Hawaii Carbon Assessment by simulating future land cover scenarios. The resulting scenarios used measures of invasive species spread and fire-driven forest loss to compare baseline conditions of current ecosystem protection (Protection) with “No Protection”, and “Protection and Restoration” for years 2070-2100. Using the land cover scenarios as an input to the ecosystem services models the results for water yield and sediment yield benefits are provided as the difference between worse case scenario and protection scenarios, each as a raster of per pixel change and the reef productivity, or estimated fish catch per ha, is provided as a shapefile summarized by Moku (Hawaiian Land Division), only for the difference between Targeted Protection and No Protection.

We integrated recent climate model projections developed for the State of Hawai’i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (Tmin, Tmean, Tmax) and mean precipitation (Pmean) data at 250 m resolution. We used observation-based data for the baseline bioclimatic variables from the Rainfall Atlas of Hawai’i. We used the most up-to-date dynamically downscaled future projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two projections into a suite of 19 bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions specifically for the Hawaiian Islands. These bioclimatic variables are available state-wide for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under RCP 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections). Aside from these typical bioclimatic variables, we also calculated annual and mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate. As Hawai’i is characterized by two 6-month seasons, we also provide mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate.

We integrated recent climate model projections developed for the State of Hawai’i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (Tmin, Tmean, Tmax) and mean precipitation (Pmean) data at 250 m resolution. We used observation-based data for the baseline bioclimatic variables from the Rainfall Atlas of Hawai’i. We used the most up-to-date dynamically downscaled future projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two projections into a suite of 19 bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions specifically for the Hawaiian Islands. These bioclimatic variables are available state-wide for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under RCP 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections). Aside from these typical bioclimatic variables, we also calculated annual and mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate. As Hawai’i is characterized by two 6-month seasons, we also provide mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate.

We integrated recent climate model projections developed for the State of Hawai’i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (Tmin, Tmean, Tmax) and mean precipitation (Pmean) data at 250 m resolution. We used observation-based data for the baseline bioclimatic variables from the Rainfall Atlas of Hawai’i. We used the most up-to-date dynamically downscaled future projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two projections into a suite of 19 bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions specifically for the Hawaiian Islands. These bioclimatic variables are available state-wide for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under RCP 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections). As Hawai’i is characterized by two 6-month seasons, we also provide mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate.