Fig 1.
Average annual landings by species groups by dollar value and tonnage.
Arranged by species group for Atlantic Canadian fisheries for 1991–2010. Dollar values are normalised to year 2000 dollars and are in millions of dollars, weights are presented in thousands of tonnes (both data types use the same axis). Includes production from aquaculture. Note, in these data ‘shellfish’ encompasses all harvested marine invertebrate species.
Fig 2.
Eastern Canada as it relates to the Northwest Atlantic Fisheries Organization (NAFO) fishing areas with DFO management areas overlaid.
For clarity approximate provincial borders have been emphasised in dark blue, U.S. and Canada border has been emphasised in black. In this assessment Gulf and Quebec management areas were treated as a single unit (figure modified from [25]).
Table 1.
Schematic representation of data configuration for each species, s.
Each of the 12 configurations yielded a separate global distribution of catch potential in half-degree latitude by half-degree longitude cells for each year, Y that was modelled (1950–2100).
Fig 3.
Geographic coverage of datasets.
Grid lines indicate individual half-degree latitude/longitude data cells. White boundary line outlines study area (i.e., Canadian Atlantic EEZ). Data outside of this boundary was truncated from the datasets before aggregating management area data. Cell colours define data aggregation layer for DBEM outputs: Newfoundland and Labrador management area is represented by dark green cells; Maritime management area is represented by light green cells, and Gulf (including Quebec) management area is represented by the yellow-green cells. Inclusion of land area within data aggregation is irrelevant, as these cells do not contain any data. Coastline data from: [41].
Fig 4.
Framework for the impact index demonstrating relationship between components.
Elements at each branch are equally weighted to other items at the same level as indicated by bracketed numbers.
Table 2.
Cumulative exposure indicator of future changes in fisheries (before normalisation of values).
Values in fourth and fifth columns are the indicator scores (i.e., the relative change in landings scaled by proportional value of the individual species). For integration into the impact index, the exposure scores were reversed and then normalised to score between 0 and 1, so that declines in landings earned a high score and implied a high exposure to OA and climate change.
Fig 5.
Breakdown of total shellfish average annual landings value.
Data represent the average annual value from 1991–2010. Top seven most valuable species are indicated by data labels. The remaining shellfish species include other crab species (i.e., not snow crab), sea urchin, whelks and sea cucumber as well as ‘other shellfish,’ which together amount to 1.5% of the total value. Note that ‘clams’ refers to several species, however Stimpsons’ Surf Clam is by far the largest fraction of this group.
Fig 6.
Comparison of model outputs with OA (red) and without OA (blue) effects through the century, under both climate scenarios (RCP 2.6 as solid lines, RCP 8.5 as dotted lines) for whole Atlantic Canadian EEZ.
Values are relative changes in catch potential. Note different axes between sub-plots. (S1 Fig. contains relative changes in distribution for both ‘with OA’ and ‘without OA’ treatments). Lines represent multi-model medians from outputs of three earth system models (GFDL, IPSL, MPI).
Fig 7.
Changes in landing weight for projection scenarios for each species in the three DFO management areas and across the total Atlantic region.
Each set of bars from left to right presents the year 2000 catch weight (pale blue), 2050 projected catch (yellow), and 2090 projected catch (green). Sections of each bar with diagonal hashes denote the RCP 8.5 climate scenario projections; the solid (semi-transparent) sections indicate the RCP 2.6 projections. The projected changes for the total regional landings are based on the relative change calculated across the whole study region and therefore do not present the sum of the projected landings from the individual management areas. DBEM relative change projections as percent change for each species in each time-step/climate scenario are available in S1 Table.
Fig 8.
Relative changes in distribution for selected commercially targeted shellfish species.
Northern shrimp (a -top), American oyster (b—middle) and snow crab (c—bottom), for 2050 (left) and 2090 (right) under RCP 8.5, highlighting south to north trend of changing species distributions. Colour scales indicate relative change predicted by DBEM for each half-degree latitude by half-degree longitude cell and do not indicate absolute values. Darkest shades (in both directions) correspond to cells with low absolute values, where small absolute changes result in large relative changes (e.g., a shift of 1T to 2T results in a 100% increase, while a change of 10T to 15T only leads to a 50% increase). Changes that exceeded +100% were set to 100% to maintain coherent colour scales. See S1 Fig for baseline DBEM distributions and figures for other species and climate treatments.
Table 3.
Indicators scores for sensitivity.
Columns 2–3 present absolute scores for each province while columns 4–5 present the corresponding normalised scores as used to calculate provincial sensitivity (column 6). Higher sensitivity scores contribute to higher potential impact. The sensitivity scores were combined with the adaptive capacity scores (as indicated in Fig 4) in Table 4 to define vulnerability for each province (Table 5).
Table 4.
Indicators scores for adaptive capacity.
Columns 2–4 present absolute scores for each indicator. Normalised indicators were reversed (i.e., subtracted from 1.0) (columns 5–7), so that low indicator scores contributed to higher potential. The combined adaptive capacity score (last column) is the average of the reversed, normalised indicators. Adaptive capacity scores were combined with the sensitivity scores (as indicated in Fig 4) in Table 3 to define vulnerability for each province (Table 5).
Table 5.
Impact index components and scores.
Components are presented as final normalised scores. The exposure scores are presented in columns 3–4 as quartets of climate scenario and future time-step. The vulnerability scores (column 5) are the average (i.e., equally weighted combination) of sensitivity (Table 3) and adaptive capacity (Table 4) as indicated by Fig 4. The final index score quartets (column 6–7) are the average (i.e., equally weighted combination) of the relevant exposures and vulnerabilities. The final two columns indicate rank for each unique potential impact score: 1-high, 2-moderate, 3-low, 4-minimal and 5-least potential for impact (all categories except 3-low, represent 6 unique scores– 3-low only represents 4 unique scores).