Six metrics were used to determine Population Vulnerability: global population size, annual occurrence in the California Current System (CCS), percent of the population present in the CCS, threat status, breeding score, and annual adult survival. Global Population size (POP)—to determine population size estimates for each species we gathered information tabulated by American Bird Conservancy, Birdlife International, and other primary sources. Proportion of Population in CCS (CCSpop)—for each species, we generated the population size within the CCS by averaging region-wide population estimates, or by combining state estimates for California, Oregon, and Washington for each species (if estimates were not available for a region or state, “NA” was recorded in place of a value) and then dividing the CCSpop value by the estimated global population size (POP) to yield the percentage of the population occurring in the CCS. Annual Occurrence in the CCS (AO)—for each species, we estimated the number of months per year within the CCS and binned this estimate into three categories: 1–4 months, 5–8 months, or 9–12 months. Threat Status (TS)—for each species, we used the International Union for Conservation of Nature (IUCN) species threat status (IUCN 2014) and the U.S. Fish and Wildlife national threat status lists (USFWS 2014) to determine TS values for each species. If available, we also evaluated threat status values from state and international agencies. Breeding Score (BR)—we determined the degree to which a species breeds and feeds its young in the CCS according to 3 categories: breeds in the CCS, may breed in the CCS, or does not breed in the CCS. Adult Survival (AS)—for each species, we referenced information to estimate adult annual survival, because adult survival among marine birds in general is the most important demographic factor that can affect population growth rate and therefore inform vulnerability. These data support the following publication: Adams, J., Kelsey, E.C., Felis J.J., and Pereksta, D.M., 2016, Collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure: U.S. Geological Survey Open-File Report 2016-1154, 116 p., https://doi.org/10.3133/ofr20161154. These data were revisied in June 2017 and the revision published in August 2017. Please be advised to use CCS_vulnerability_FINAL_VERSION_v9_PV.csv

Layers that present various important parameters such as inventories, presence, sightings, distribution, relative occurrence or catch rates, critical habitat, breeding and feeding areas, potential spawning and haul-out sites for the different species with status under the Species at Risk Act (SARA). The act classifies those species as being either extirpated, endangered, threatened, or of special concern. Under SARA, Fisheries and Oceans Canada must produce recovery strategies and action plans for aquatic species listed as endangered or threatened. The act is part of Canada’s strategy to protect hundreds of wild plants and animal species from becoming extinct, and to help in their recovery. The different species represented by the layers are the following: 1. American shad (Alosa sapidissima) 2. Atlantic sturgeon (Acipenser oxyrinchus) 3. Atlantic wolffish (Anarhichas lupus) 4. Beluga whale (Delphinapterus leucas) 5. Blue whale (Balaenoptera musculus) 6. Copper redhorse (Moxostoma hubbsi) 7. Eelgrass (Zostera marina) 8. Grey seal (Halichoerus grypus) 9. Harbor seal (Phoca vitulina) 10. Humpback whale (Megaptera novaeangliae) 11. Lake sturgeon (Acipenser fulvescens) 12. Lumpfish (Cyclopterus lumpus) 13. Northern wolffish (Anarhichas denticulatus) 14. Rainbow smelt (Osmerus mordax) 15. Sea pens (Pennatulacea) 16. Seaweed 17. Smooth skate (Malacoraja senta) 18. Sponges 19. Spotted wolffish (Anarhichas minor) 20. Striped bass (Morone saxatilis) 21. Thorny skate (Amblyraja radiata) 22. Winter skate (Leucoraja ocellata)

Increased water temperature from global climate change may exacerbate existing stresses to eelgrass (Zostera marina) meadows throughout the northeastern United States, possibly leading to declines in populations. In this study, we developed a data-driven model to estimate how seagrass distribution and abundance will likely change with expected temperature increases under climate-change scenarios and applied the model to Pleasant Bay, Massachusetts. Long-term seagrass and water quality monitoring data along with satellite temperature data were used to generate the spatial distribution of environmental drivers across the Bay. These data were then used in a 0-D point-model that incorporated both empirical and mechanistic relationships to predict future spatial seagrass distribution and abundance assuming increases of 1.2°C and 1.95°C by the year 2050. The model demonstrated decline in distribution and abundance with increasing temperature alongside estimated 49 to 93% reductions in biomass. There was a complete loss of regions able to sustain seagrass under the highest temperature scenario. Most of the predicted loss occurred along the shallow and deep edges of the meadows effectively squeezing eelgrass into a narrow depth range where both light and temperature conditions remain favorable for eelgrass growth. These results are intended to help inform the development of targeted conservation and management actions to address the region-wide downward trajectory and facilitate recovery.

Globally, terrestrially-breeding marine predators have experienced shifts in species distribution, prey availability, breeding phenology, and population dynamics due to climate change. These central-place foragers are restricted within proximity of their breeding colonies during the breeding season, making them highly susceptible to any changes in both marine and terrestrial environments. While ecologists have developed risk assessments to assess likely climate risk in various contexts, these often overlook critical breeding biology data. To address this knowledge gap, we developed a trait-based risk assessment framework, focusing on the breeding season and applying it to marine predators breeding in parts of Australian territory and Antarctica. Our objectives were to quantify climate change risk, identify specific threats, and establish an adaptable framework. The assessment considered 25 criteria related to three risk components: vulnerability, exposure, and hazard, while accounting for uncertainty. We employed a scoring system that integrated a systematic literature review and expert elicitation for the hazard criteria. Monte Carlo sensitivity analysis was conducted to identify key factors contributing to overall risk. Our results identified shy albatross (Thalassarche cauta), southern rockhopper penguins (Eudyptes chrysocome), Australian fur seals (Arctocephalus pusillus doriferus), and Australian sea lions (Neophoca cinerea) with high climate urgency. Species breeding in lower latitudes as well as certain eared seal, albatross, and penguin species were particularly at risk. Hazard and exposure explained the most variation in relative risk, outweighing vulnerability. Key climate hazards affecting most species include extreme weather events, changes in habitat suitability, and prey availability. We emphasise the need for further research, focusing on at-risk species, and filling knowledge gaps (less-studied hazard criteria, and/or species) to provide a more accurate and robust climate change risk assessment. Our findings offer valuable insights for conservation efforts, given monitoring and implementing climate adaptation strategies for land-dependent marine predators is more feasible during their breeding season.

This data set contains genetic information collected from eelgrass (Zostera marina) populations along the Pacific coast of North America from Alaska to Baha California. A total of 447 samples were collected comprising 401 unique individuals (genets) and 46 clones (ramets) from which 10 microsatellite DNA loci were obtained.

The goal of the tidal-fluvial estuary study is to determine the estuary's contribution to the spatial structure and life history diversity of Columbia River salmon stocks and the implications for estuary restoration. The study targets salmon use of tidal-fresh habitats in the estuary from Rkm 75 to Bonneville Dam, and addresses four primary objectives: 1. Characterize the temporal and spatial distribution of Chinook salmon genetic stock groups throughout the estuary (March 2010 - March 2012). 2. Determine stock-specific habitat use, life histories, and performance of juvenile salmon in key habitat complexes to fill data gaps in the tidal fluvial reaches of the estuary (2012-2016). 3. Monitor juvenile salmon life histories and their contributions to adult returns in selected estuary tributaries, including tributary examples where tidal habitats have been restored (2012-2018). 4. Evaluate estuary restoration needs for recovery of all salmon ESUs and account for projected effects of climate change through application of a salmon life-cycle model (2011-1015). The study, funded by the U.S. Army Corps of Engineers, involves a large team of researchers organized by NOAA Fisheries, including researchers from the Oregon Health and Sciences University, University of Washington, and Washington Department of Fish and Wildlife. The study addresses critical uncertainties identified in the research, monitoring, and evaluation (RME) program for the Federal Columbia River Estuary Program (FCREP). The Estuary Program is intended to conserve and restore the estuary ecosystem to improve the performance of listed salmonid populations. Products from the tidal-fluvial study will include: 1. Descriptions of stock-specific temporal and spatial distributions of Chinook salmon throughout the estuary. 2. Estimates of variations in Chinook salmon stock composition and stock-specific growth, food habits, consumption rates, and bioenergetic efficiencies within selected tidal-fluvial habitats. 3. Estimated contributions of estuarine life histories among returning adult Chinook salmon from selected populations throughout the Columbia River Basin. 4. A hydrological model quantifying the dynamics of rearing habitat opportunities for juvenile salmon at estuary reach and habitat scales. 5. Improved life-cycle models to account for the estuarine life histories of juvenile salmon and estimating the potential effectiveness of estuary restoration actions on the recovery and viability of selected salmon stocks. These results will directly address information needs to support estuary actions specified in the Federal Columbia River Power System (FCRPS) Biological Opinion for the Columbia River. The tidal-fluvial estuary study is part of an ongoing estuary research program initiated in 2002. The current study expands upon earlier research conducted in the lower 100 km of the estuary from 2002 to 2008. Although all objectives will be addressed by 2018 to correspond with a review of progress implementing the FCRPS Biological Opinion, some sampling activities may extend beyond this date to allow brood-year reconstruction of estuary contributions to adult returns in selected streams (Objective 3). Bimonthly genetic stock group distribution for juvenile Chinook Salmon collected from 3 habitats each from 6 tidal-fluvial estuary reaches and monthly fish species composition, abundance, and length:weight; Chinook salmon life history and genetic stock ID.

These datasets include the components of and results from the Rarity and Climate Sensitivity Index (RCS) and occurrence records used to calculate the index for 29 stream fishes native to the Pacific Northwest (Washington, Idaho, Oregon) of the United States. The RCS is an index that ranks species’ intrinsic sensitivity to climate change based on their area of occurrence and climate niche breadth, the range of environmental conditions for a given species. The RCS uses point occurrences to calculate both metrics. We compiled point occurrences from a variety of sources. Final point occurrences were filtered for quality assurance and received expert review (details in occurrence dataset metadata). We calculated RCS metrics at two spatial grains: 1) Hydrologic Unit Code (HUC) level 12 watersheds and 2) 1 km buffered occurrence points and stream segment level. The area of occurrence for each species was calculated as the total watershed area of all HUC 12 watersheds containing any of the final set of occurrence points or the total area of 1 km buffer around the final set of occurrence points. We calculated climate niche breadth using two sets of environmental variables at both spatial grains, bioclimatic and stream level. Bioclimatic level was calculated by extracting annual mean precipitation, maximum temperature of the warmest month, and minimum temperature of the coldest month from the area of occurrence using the the Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset. Stream level was calculated by extracting mean August stream temperature, mean stream baseflow, and either predicted streamflow permanence probability or predicted streamflow permanence class from all streams within the watershed area of occurrence or the nearest stream to each point occurrence for the 1 km grain. Stream level data was extracted using compiled streamflow permanence, water temperature, and modeled streamflow data (Sando and Schultz, 2022). Climate niche breadth from both levels is calculated as the area-weighted standard deviation for each variable. The RCS is calculated from the scaled and combined species’ area of occurrence and climate niche breadth, such that an intrinsically sensitive species has a small area of occurrence and a narrow niche breadth.

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Two metrics were used to determine Collision Vulnerability: Macro-avoidance and habitat flexibility. Macro-avoidance (MA)—The macro-avoidance values for species indicate the species-specific probability of avoidance for birds associated with wind power infrastructure. For each species, we derived this value from observed macro-avoidance rates (via human observation and radar) at existing offshore wind power sites. In cases where species-specific data were not available, we used information from similar taxa. Habitat Flexibility (HF)—the degree to which a species shows habitat-specific feeding strategies (habitat flexibility) influences its vulnerability for displacement by offshore infrastructure. We evaluated literature involving diet, feeding habits, and habitat use to estimate HF or each marine bird species in the CCS database. These data support the following publication: Adams, J., Kelsey, E.C., Felis J.J., and Pereksta, D.M., 2016, Collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure: U.S. Geological Survey Open-File Report 2016-1154, 116 p., https://doi.org/10.3133/ofr20161154. These data were revisied in June 2017 and the revision published in August 2017. Please be advised to use CCS_vulnerability_FINAL_VERSION_v10_DV.csv