The Marine Biodiversity Observation Network Pole to Pole (MBON P2P) effort seeks to develop a framework for the collection, use and sharing of marine biodiversity data in a coordinated, standardized manner leveraging on existing infrastructure managed by the Global Ocean Observing System (GOOS; IOC-UNESCO), the GEO Biodiversity Observation Network (GEO BON), and the Ocean Biogeographic Information System (OBIS). The MBON Pole to Pole aims to become a key resource for decision-making and management of living resource across countries in the Americas for reporting requirements under the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Aichi Targets of the Convention of Biological Diversity (CBD), and the UN 2030 Agenda for Sustainable Development Goals (SDGs).This collection corresponds to the species registered on sandy beaches of the Musquash Harbour, Mispec Bay, and New River Beach, New Brunswick, Canada, using the MBON P2P sampling protocol for sandy beaches, with funding from the Government of Canada's Coastal Environmental Baseline Program.Citation: Reinhart B, Jonah L (2025). MBON POLE TO POLE: SANDY BEACH BIODIVERSITY OF SOUTHWEST NEW BRUNSWICK, CANADA. Version 1.7. Caribbean OBIS Node. Samplingevent dataset. https://ipt.iobis.org/mbon/resource?r=sandybeachesbayoffundynb&v=1.7

The Marine Biodiversity Observation Network Pole to Pole (MBON P2P) effort seeks to develop a framework for the collection, use and sharing of marine biodiversity data in a coordinated, standardized manner leveraging on existing infrastructure managed by the Global Ocean Observing System (GOOS; IOC-UNESCO), the GEO Biodiversity Observation Network (GEO BON), and the Ocean Biogeographic Information System (OBIS). The MBON Pole to Pole aims to become a key resource for decision-making and management of living resource across countries in the Americas for reporting requirements under the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Aichi Targets of the Convention of Biological Diversity (CBD), and the UN 2030 Agenda for Sustainable Development Goals (SDGs).This collection corresponds to the species registered on rocky shores of the Musquash Harbour, Passamaquoddy Bay and Mispec Bay, New Brunswick, Canada, using the MBON P2P sampling protocol for rocky shores, with funding from the Government of Canada's Coastal Environmental Baseline Program.Citation: Reinhart B, Cooper A, Nason R, Jonah L (2025). MBON POLE TO POLE: ROCKY SHORE BIODIVERSITY OF MUSQUASH HARBOUR, PASSAMAQUODDY BAY AND MISPEC BAY. Version 1.7. Caribbean OBIS Node. Samplingevent dataset. https://ipt.iobis.org/mbon/resource?r=rockyshoresbayoffundynb&v=1.7

Data represents surface water occurrence frequency (percentage), which describes the frequency for each grid appeared as water in the 30 years time period of 1991 to 2020. The data covers Canada’s entire landmass including all transboundary watersheds, and is at 30-meter spatial resolution. The surface water occurrence frequency is derived using the surface water model of Wang et al. (2023) from all-available monthly water data observed by the Landsat satellites (Pekel et al., 2016). Here, permanent waters are represented by 100%, and permanent land surfaces by 0%, of water occurrence for a 30-meter by 30-meter grid.References:Pekel, J.-F., A. Cottam, N. Gorelick, A.S. Belward, 2016, High-resolution mapping of global surface water and its long-term changes. Nature, 540, 418-422.Wang, S., J. Li, and H. A. J. Russell, 2023, Methods for Estimating Surface Water Storage Changes and Their Evaluations. Journal of Hydrometeorology, DOI: https://doi.org/10.1175/JHM-D-22-0098.1.

This polygon layer displays ensemble-based, medium-range precipitation forecasts from the Global Ensemble Prediction System (GEPS), offering a probabilistic view of future rainfall or snowfall over a 16‑day horizon. It aids in uncertainty analysis, risk assessment, and strategic resource planning.Ensemble Approach: GEPS runs multiple perturbed members of ECCC’s GEM model, capturing a range of atmospheric evolutions and yielding probability distributions for precipitation. Global Domain: Similar coverage to the GDPS but focuses on ensemble mean, spreads, and probabilities rather than a single deterministic outcome. Longer-Range Outlook: Extends up to 16 days, supporting risk-based planning for potential floods, extended rainfall events, or dryness. Data Utility: Allows decision-makers to weigh confidence levels in precipitation scenarios, vital for water management, agriculture, and emergency contingency strategies.

The Standardized Precipitation Evapotranspiration Index (SPEI) is computed similarly to the SPI. The main difference is that SPI assesses precipitation variance, while SPEI also considers demand from evapotranspiration which is subtracted from any precipitation accumulation prior to assessment.Unlike the SPI, the SPEI captures the main impact of increased temperatures on water demand.

Drought is a deficiency in precipitation over an extended period, usually a season or more, resulting in a water shortage that has adverse impacts on vegetation, animals and/or people. The Climate Moisture Index (CMI) was calculated as the difference between annual precipitation and potential evapotranspiration (PET) – the potential loss of water vapour from a landscape covered by vegetation. Positive CMI values indicate wet or moist conditions and show that precipitation is sufficient to sustain a closed-canopy forest. Negative CMI values indicate dry conditions that, at best, can support discontinuous parkland-type forests. The CMI is well suited to evaluating moisture conditions in dry regions such as the Prairie Provinces and has been used for other ecological studies.Mean annual potential evapotranspiration (PET) was estimated for 30-year periods using the modified Penman-Monteith formulation of Hogg (1997), based on monthly 10-km gridded temperature data. Data shown on maps are 30-year averages. Historical values of CMI (1981-2010) were created by averaging annual CMI calculated from interpolated monthly temperature and precipitation data produced from climate station records. Future values of CMI were projected from downscaled monthly values of temperature and precipitation simulated using the Canadian Earth System Model version 2 (CanESM2) for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century.Provided layer: mean annual Climate Moisture Index across Canada for a reference period (1981-2010).Reference: Hogg, E.H. 1997. Temporal scaling of moisture and the forest-grassland boundary in western Canada. Agricultural and Forest Meteorology 84,115–122.

The Homogenized Surface Pressure data consist of monthly, seasonal and annual means of hourly sea level and station pressure (hectopascals) for 626 locations in Canada. Homogenized climate data incorporate adjustments (derived from statistical procedures) to the original station data to account for discontinuities from non-climatic factors, such as instrument changes or station relocation. The time periods of the data vary by location, with the oldest data available from 1953 at some stations to the most recent update in 2014. Data availability over most of the Canadian Arctic is restricted to 1953 to present. The data will continue to be updated every few years (as time permits).

Shows sub-basin-averaged precipitation from the GEPS ensemble, reflecting the mean (or other metrics) of multiple ensemble members. Useful to understand probabilistic rainfall/snowfall expectations for each watershed.GEPS is ECCC’s ensemble system, running ~20 members globally to quantify forecast uncertainty out to ~16 days. This layer aggregates ensemble precipitation data over sub-basin polygons. The attribute “Average Accumulated Precipitation” often represents the ensemble mean, capturing a more probable average scenario. Operators can use this for risk-based hydrological planning or to gauge confidence in upcoming flood/drought scenarios across different sub-basins.

This dataset is a compilation of numerous data files recovered as part of a data request in 2024 from a historical archive of DFO research data. Sediment and Suspended Particulate Matter (SPM) samples were collected over more than a decade as part of Dr. Douglas Loring’s research program while working at the Bedford Institute of Oceanography (BIO). Samples were collected as part of individual and collaborative research projects, and links to the relevant primary science publications and reports are included in the data in an effort to provide context to the data, as well as describe the field and laboratory techniques used to generate the attached data.

Moored instrument time series data include current velocity, temperature, salinity, oxygen, fluorescence, transmissivity, turbidity, and particle capture of carbon, nitrogen, and silicon as well as sediment trap, ice drift and ice draft data.These data were collected by researchers from the Institute of Ocean Sciences, Sidney, BC, from locations ranging from the North Pacific, the Beaufort Sea, and across the Canadian Arctic Archipelago to Baffin Bay.