Bio-ORACLE is a set of GIS rasters providing geophysical, biotic and environmental data for surface and benthic marine realms. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).

Linking biodiversity occurrence data to the physical and biotic environment provides a framework to formulate hypotheses about the ecological processes governing spatial and temporal patterns in biodiversity, which can be useful for marine ecosystem management and conservation.

Bio-ORACLE offers a user-friendly solution to accomplish this task by providing 18 global geophysical, biotic and climate layers at a common spatial resolution (5 arcmin) and a uniform landmask.

The data available in Bio-ORACLE are documented in two peer reviewed articles that you should cite: Tyberghein L, Verbruggen H, Pauly K, Troupin C, Mineur F, De Clerck O (2012) Bio-ORACLE: A global environmental dataset for marine species distribution modelling. Global Ecology and Biogeography, 21, 272–281. Assis, J., Tyberghein, L., Bosh, S., Verbruggen, H., Serrão, E. A., & De Clerck, O. (2017). Bio-ORACLE v2.0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography.

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.7.3,hdf5=1.10.4 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=Baseline geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2021-12-17 18:07:53 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=sea_water_ph_reported_on_total_scale standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2010-01-01T00:00:00Z time_coverage_start=2000-01-01T00:00:00Z Westernmost_Easting=-179.975

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.7.3,hdf5=1.10.4 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=NA geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2022-03-23 20:38:21 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org keywords_vocabulary=GCMD Science Keywords Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=terrain_characteristics standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=1970-01-01T00:00:00Z time_coverage_start=1970-01-01T00:00:00Z Westernmost_Easting=-179.975

Uses attributes recommended by https://cfconventions.org cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.6, COARDS, ACDD-1.3 Easternmost_Easting=180.0 experiment=Baseline geospatial_lat_max=90.0 geospatial_lat_min=-90.0 geospatial_lat_resolution=0.05001389274798555 geospatial_lat_units=degrees_north geospatial_lon_max=180.0 geospatial_lon_min=-180.0 geospatial_lon_resolution=0.0500069454090846 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.08333333333333333 0 90 0 -0.08333333333333333 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2021-12-06 23:31:17 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org Northernmost_Northing=90.0 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-90.0 standard_name=sea_water_temperature standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2010-01-01T00:00:00Z time_coverage_start=2000-01-01T00:00:00Z Westernmost_Easting=-180.0

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.7.3,hdf5=1.10.4 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=Baseline geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2022-05-03 13:22:24 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org keywords_vocabulary=GCMD Science Keywords Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=cloud_area_fraction standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2010-01-01T00:00:00Z time_coverage_start=2000-01-01T00:00:00Z Westernmost_Easting=-179.975

The Caspian Sea hosts unique native and endemic faunas. However, it is also source and sink of invasive alien species (IAS) with some listed among the worst 100 invasive species by the IUCN. A common approach to study biodiversity and biogeographic patterns or to predict the invasive potential of species is the application of ecological niche models and species distribution models. These are statistical methods using spatially gridded environmental data and species occurrence information. As the Caspian Sea is not connected to the world oceans, spatially gridded environmental data for the Caspian Sea are not available in the widely used Bio-ORACLE marine data set. To address this issue, we compiled 28 ecologically relevant spatially gridded environmental variables using Kriging interpolation of point data to model minimum, maximum, mean and range of temperature, salinity and dissolved oxygen for the surface and benthic zones of the Caspian Sea. Data were retrieved from the World Ocean Dataset. Additionally, we utilized raster statistics to create surface layers of maximum, mean, minimum and range of chlorophyll a from remotely sensed data. We developed these environmental variables as they were previously confirmed to be relevant for the biogeographical classification of the Caspian Sea. To allow projections of models across the world oceans into the Caspian Sea (and vice versa), we matched our raster dimensions with those of the Bio-ORACLE data set. Our extension of the Bio-ORACLE data set with data from the Caspian Sea provides an important basis for the monitoring and evaluation of suitable habitats for native species as well as predicting the invasive potential of Caspian Sea species into the World oceans.

Keywords: Sea surface temperature, salinity, oxygen, Chlorophyll a, ecological modelling, invasive alien species

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.7.3,hdf5=1.10.4 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=ssp370 geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2022-06-08 21:12:41 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=sea_ice_area_fraction standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2090-01-01T00:00:00Z time_coverage_start=2020-01-01T00:00:00Z Westernmost_Easting=-179.975

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.7.3,hdf5=1.10.4 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=ssp460 geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2023-01-26 13:23:51 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=ocean_mixed_layer_thickness standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2090-01-01T00:00:00Z time_coverage_start=2020-01-01T00:00:00Z Westernmost_Easting=-179.975

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.7.3,hdf5=1.10.4 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=Baseline geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2021-12-14 17:02:48 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org keywords_vocabulary=GCMD Science Keywords Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=sea_water_salinity standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2010-01-01T00:00:00Z time_coverage_start=2000-01-01T00:00:00Z Westernmost_Easting=-179.975

Population & Environmental data: latgrad_pop_env.csv

Sample ID, site ID and Environmental data for variables used in lfmm and RDA analysis

id = sample ID

site = site ID

LT_meantemp = long term annual mean temperature, calculated from https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.html

LT_rangetemp = Long term annual mean temperature range, calculated from https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.html

BO_damean = mean diffuse attenuation, downloaded from Bio-ORACLE v2.0 (Assis et al., 2018)

BO2_curvelmean_bdmax = mean seawater velocity at depth, downloaded from Bio-ORACLE v2.0 (Assis et al., 2018)

SNP datafile: latgrad_bayescan_nodup

Bayescan input file

SNP datafile: latgrad_geno

Snmf input file in geno format, missing values are coded as 9

SNP datafile: latgrad_imputed

SNP input file, imputed with snmf and used for lfmm, RDA and GF analysis

The global distribution of primary production and consumption by humans (fisheries) is well-documented, but we have no map linking the central ecological process of consumption within food webs to temperature and other ecological drivers. Using standardized assays that span 105° of latitude on four continents, we show that rates of bait consumption by generalist predators in shallow marine ecosystems are tightly linked to both temperature and the composition of consumer assemblages. Unexpectedly, rates of consumption peaked at midlatitudes (25 to 35°) in both Northern and Southern Hemispheres across both seagrass and unvegetated sediment habitats. This pattern contrasts with terrestrial systems, where biotic interactions reportedly weaken away from the equator, but it parallels an emerging pattern of a subtropical peak in marine biodiversity. The higher consumption at midlatitudes was closely related to the type of consumers present, which explained rates of consumption better than consumer density, biomass, species diversity, or habitat. Indeed, the apparent effect of temperature on consumption was mostly driven by temperature-associated turnover in consumer community composition. Our findings reinforce the key influence of climate warming on altered species composition and highlight its implications for the functioning of Earth’s ecosystems. Methods The core data for this project consist of 1) results of marine consumption assays in which small pieces of squid were tethered to stacks (squidpops) and placed inside and outside of shallow seagrass meadows, 3) water tempearture records collected at the time of the assays, 2) counts from surveys of consumers (fish and large invertebrates) using hand-pulled seines, and 3) summaries of surveys of consumers and their interactions with squidpops collected using underwater videography. These core data are included in their rawest form. Various data summaries produced in R are also included. See Usage Notes below about location of R scripts. Data for several explanatory variables were accessed from sources external to the project and the core dataset. The pieces of data used in the project are included in this dataset and they can be summarized as follows:

environmental variables from Bio-ORACLE human population densities from the Gridded Population of the World fishing pressure data from the Sea Around Us project taxonomy and species traits from FishBase and the Reef Life Survey

In addition to raw data and pre-processed external data, we include a compilation of data from multiple sources that were used in statstical modeling analysis for the paper. More information on individual data files and their contents, please see the accompanying README.md file.

Nutrient data were obtained from the Bio-ORACLE project and represent a long-term composite of data from 2000 to 2014. The map layer represents mean silicate concentration (micromoles per liter) in surface waters of the U.S. Exclusive Economic Zone. Additional data available for download here provide six nutrient concentrations at three different depths within the water column (surface, mean depth, and maximum depth). Data have a common spatial resolution of 5 arc minutes and were assessed using a cross†validation framework against in situ quality†controlled data.

Environmental variables in the region of the Kerguelen Plateau compiled from different sources and provided in the ascii raster format. Mean surface and seafloor temperature, salinity and their respective amplitude data are available on the time coverage 1955-2012 and over five decades: 1955 to 1964, 1965 to 1974, 1975 to 1984, 1985 to 1994 and 1995 to 2012. N/A was set as the no data reference. Future projections are provided for several parameters: they were modified after the Bio-ORACLE database (Tyberghein et al. 2012). They are based on three IPCC scenarii (B1, AIB, A2) for years 2100 and 2200 (IPCC, 4th report).

Nutrient data were obtained from the Bio-ORACLE project and represent a long-term composite of data from 2000 to 2014. The map layer represents mean nitrate concentration (micromoles per liter) in surface waters of the U.S. Exclusive Economic Zone. Additional data available for download here provide six nutrient concentrations at three different depths within the water column (surface, mean dep...

Diseases are ubiquitous in natural systems, with broad effects across populations, communities, and ecosystems. However, the drivers of many diseases remain poorly understood, particularly in marine environments, inhibiting effective conservation and management measures. We examined biogeographic patterns of infection in the foundational seagrass Zostera marina by the parasitic protist Labyrinthula zosterae, the causative agent of seagrass wasting disease, across >20° of latitude in two ocean basins. We then identified and characterized relationships among wasting disease prevalence and a suite of host traits and environmental variables. Host characteristics and transmission dynamics explained most of the variance in prevalence across our survey, yet the particular host traits underlying these relationships varied between oceans, with host size and nitrogen content important in the Pacific and host size and density most important in the Atlantic. Temperature was also a key predictor of prevalence, particularly in the Pacific Ocean. The strength and shape of the relationships between prevalence and some predictors differed in our large-scale survey vs previous experimental and site-specific work. These results show that both host characteristics and environment influence host-parasite interactions, and that some such effects scale up predictably, whereas others appear to depend on regional or local context. Methods Study sites: In the summer of 2015, we surveyed 17 discrete, monospecific eelgrass beds across the northern hemisphere, mostly along the coasts of North America (9 in the Atlantic Ocean, 8 in the Pacific Ocean). All of the surveyed sites were in protected, shallow waters (0 - 2 m depth at low tide). Wasting disease survey: At each site, we collected a total of 20 individual vegetative eelgrass shoots at least two meters apart along two 10 meter transects running parallel to shore. We clipped shoots at the base in the field and placed them in individual plastic bags. We timed sampling to target peak wasting disease prevalence based on local knowledge of system dynamics, which resulted in most sites being surveyed in mid-summer near peak eelgrass biomass. Within five hours of collection in the field, we scored the third youngest leaf of each shoot for signs of wasting disease (i.e., lesions). We focused on this leaf because it has been shown to harbor the highest intensity of wasting disease (Bockelmann et al. 2013) and remains sufficiently free of epibionts, making lesions clearly distinguishable. At each site, we used a standardized protocol including published descriptions and photographs of wasting disease to guide scoring (Burdick et al. 1993, Groner et al. 2014, Groner et al. 2016). Leaf lesions typically indicate intense wasting disease infections, and thus we interpret lesion distribution as a reliable reflection of L. zosterae distribution (Dawkins et al. 2018, Brakel et al. 2019). However, leaf lesions could also reflect processes other than parasite abundance. For example, though black and brown lesions are established visual signs of wasting disease, other stressors can also cause lesions, and low levels of L. zosterae parasite may be present in asymptomatic leaves (Bockelmann et al. 2013, Groner et al. 2016). Because we had local experts familiar with the signs of other stressors specific to each site (e.g., UV damage or grazing), we minimized mis-classification between lesions associated with disease and lesions caused by other stressors. We also collected notes and representative photographs of putative wasting disease lesions as necessary to ensure consistency of scoring. Host and environmental surveys: In separate surveys at these same sites in 2014, we collected data on host and environmental factors that could mediate wasting disease prevalence. These data were collected from 20, 1-m2 plots spaced roughly 2 m apart and included eelgrass density (measured as shoots per m2), blade length (measured from the meristem to the tip of the longest leaf), leaf N content (from young leaf material of 5 pooled shoots in each plot run on a CHN analyser), allelic richness (calculated from 5 shoots per plot at 24 DNA microsatellite loci), periphyton (grams of total dried algae, microbes, and detritus present on the leaf surface per grams of dried eelgrass), and mesograzer abundance (number of mesograzers per grams of eelgrass) following methods described in greater detail in Duffy et al. (2015, 2022). Many of these variables are generally consistent at a given site from year to year when sampled in the same season (Douglass et al. 2010, Bertelli et al. 2021), and sometimes consistent across many years (Reynolds et al. 2017). In addition, previous studies have demonstrated that variables measured months prior can be as or more predictive of wasting disease prevalence than those measured coincident with sampling of wasting disease (Groner et al. 2021, Graham et al. 2023). However, we may be underestimating the predictive power of host and environmental factors on wasting disease by sampling them in consecutive years rather than the same year. To quantify temperature and salinity at each site, we extracted estimates of the maximum mean monthly sea surface temperature and minimum mean monthly salinity from the Bio-ORACLE data set for 2000-2014 (Tyberghein et al. 2012, Assis et al. 2018; 9.6-km2 resolution). We chose maximum temperature to capture summer conditions when past epidemics have been observed (Rasmussen 1977, Burdick et al. 1993) and minimum salinity because lower salinities inhibit the parasite (McKone & Tanner 2009). We used the raster package in R (Hijmans 2019) to extract these data from all cells within 10 km of each site, and we averaged these estimates to generate site-level predictors. As a potential complement to these long-term data, we also measured in situ water temperature and salinity simultaneous with the wasting disease survey.

The AIMS Bioresources Library contained almost 20,000 entities, including extracts from over 7,600 samples of marine micro-organisms, frozen material and over 9,000 cryopreserved marine-derived micro-organisms. Biodiscovery is the sourcing of native biological material including plants, animals, fungi and microorganisms to identify bioactive compounds genes, enzymes and other proteins that may be used for commercial purposes such as pharmaceuticals and insecticides. AIMS has been involved in biodiscovery for 15 years and has explored Australia's mega-marine biodiversity for attributes with commercial application. The cornerstone of AIMS' biodiscovery effort is its substantial marine Bioresources Library. This collection has been sourced from over 1,500 sites across Australia.


An Oracle database for the AIMS Bioresources Library was developed to contain information of taxonomy, housekeeping (location and nature of samples including taxonomic vouchers, extracts, fractions, pure compounds, frozen cultures), and biodiscovery research history (e.g. screening and structure elucidation results, dispatches to various external parties, etc).


The database includes images most organisms and records the results of an array of bioassay tests which have varied over time with different programs and collaborators, and include anti-cancer, AIDS, anti-biotic and enzyme inhibition assays.


The taxonomic data is available for release as long as the master sample numbers are not used as unique sample identifiers, e.g. OBIS. Requests for selected data release will be considered on a case by case basis as some information is commercial in confidence and may be subject to contract conditions.


The database aimed to:
-collate taxonomic and biogeographic details
-link taxonomy and biogeography with bioactivity, and facilitate data mining
-track the use of samples in their various forms
-ensure compliance with contracts and access/benefit sharing agreements and permits
-generate reports to regulatory authorities and jurisdictions of origin, on the use of material


A subset of the data has been provided to the Ocean Biogeographic Information System (OBIS, http://iobis.org/explore/#/dataset/123l).

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.7.3,hdf5=1.10.4 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=Baseline geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2022-07-26 02:11:22 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=mole_concentration_of_phytoplankton_expressed_as_carbon_in_sea_water standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2010-01-01T00:00:00Z time_coverage_start=2000-01-01T00:00:00Z Westernmost_Easting=-179.975

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.7.3,hdf5=1.10.4 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=Baseline geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2021-12-17 02:46:45 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=mole_concentration_of_dissolved_molecular_oxygen_in_sea_water standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2010-01-01T00:00:00Z time_coverage_start=2000-01-01T00:00:00Z Westernmost_Easting=-179.975

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.7.3,hdf5=1.10.4 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=Baseline geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=File created: 2022-03-21 18:42:31 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=sea_ice_thickness standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2010-01-01T00:00:00Z time_coverage_start=2000-01-01T00:00:00Z Westernmost_Easting=-179.975

Uses attributes recommended by https://cfconventions.org _NCProperties=version=2,netcdf=4.8.1,hdf5=1.12.2 cdm_data_type=Grid comment=Uses attributes recommended by https://cfconventions.org Conventions=CF-1.5 Easternmost_Easting=179.975 experiment=ssp585 geospatial_lat_max=89.975 geospatial_lat_min=-89.975 geospatial_lat_resolution=0.049999999999999996 geospatial_lat_units=degrees_north geospatial_lon_max=179.975 geospatial_lon_min=-179.975 geospatial_lon_resolution=0.049999999999999996 geospatial_lon_units=degrees_east grid_mapping_GeoTransform=-180 0.05 0 90 0 -0.05 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=CRS definition grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 grid_mapping_spatial_ref=GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AXIS["Latitude",NORTH],AXIS["Longitude",EAST],AUTHORITY["EPSG","4326"]] history=Thu Jul 25 10:34:25 2024: ncatted -O -a long_name,swd_range,o,c,Range SeaWaterDirection swd_ssp585_Decade_2020_2100/climatologyDecadeDepthMin.nc File created: 2023-05-01 08:14:55.236471 infoUrl=https://www.bio-oracle.org institution=Bio-Oracle consortium: https://www.bio-oracle.org NCO=netCDF Operators version 5.0.6 (Homepage = http://nco.sf.net, Code = https://github.com/nco/nco) Northernmost_Northing=89.975 references=https://www.bio-oracle.org source=Bio-Oracle version V3.0 sourceUrl=(local files) Southernmost_Northing=-89.975 standard_name=sea_water_direction standard_name_vocabulary=CF Standard Name Table v70 time_coverage_end=2090-01-01T00:00:00Z time_coverage_start=2020-01-01T00:00:00Z Westernmost_Easting=-179.975