Potential socioeconomic impacts from ocean acidification and climate change effects on Atlantic Canadian fisheries

fisheries sector of the five provinces, as such the industry has a very low relevance to the econ- omy and population at large. Nova Scotia had the second lowest cumulative vulnerability score (Table 5), largely driven by strong adaptive capacity indicators (especially aquaculture and education) (Table 4). Despite having the lowest education and aquaculture indicator scores, and a consequently low adaptive capacity, NB ranked third in vulnerability due to a relatively low reliance on shellfish, and hence a low sensitivity score (Tables 3 and 4). PEI and NL were the most socially vulnerable provinces (Table 5). PEI’s vulnerability derived from having the highest sensitivity due to a comparatively small population with a rel- atively high dependence on shellfish fisheries (Table 3). Additionally, PEI had moderate scores for two of the three adaptive capacity indicators, with relatively low education and high pro- vincial unemployment (Table 4). The strong aquaculture sector in PEI was not sufficient to off- set the other indicators. NL had the lowest overall vulnerability score (Table 5). However, provincial unemployment was the only indicator where it earned the lowest provincial score (Table 4). Rather, the low overall vulnerability score was driven by generally weak scores across all the indicators, with an absence of any strong adaptive capacity or low sensitivity indicators to counterbalance the low scores. 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). Province Shellfish harvesting employment / capita(a) Shellfish value / GDP(b) Normalised shellfish employment score Normalised shellfish value score Sensitivity NB 0.013 0.008 0.21 0.18 0.19 NL 0.044 0.019 0.76 0.48 0.62 NS 0.021 0.020 0.36 0.50 0.43 PEI 0.058 0.040 1.00 1.00 1.00 Que 0.001 0.001 0.00 0.00 0.00 Data references: (a)[45–50,54,55]; (b)[20,44] https://doi.org/10.1371/journal.pone.0226544.t003 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). Province [Reciprocal] Un- employment / national un-employment(a) Post-secondary education / national post-secondary education(b) Aquaculture development / mollusc production(c) (Reversed) Normalised un- employment score (Reversed) Normalised education score (Reversed) Normalised aquaculture score (Reversed) Adaptive capacity NB 0.092 0.46 0.51 0.25 1.00 1.00 0.75

NL 0.059 0.47 0.68 1.00 0.88 0.74 0.87 NS 0.098 0.53 1.14 0.11 0.00 0.00 0.04 PEI 0.077 0.49 1.05 0.60 0.62 0.14 0.45 Que 0.103 0.52 0.80 0.00 0.18 0.54 0.24 Data reference: (a)[51]; (b)[52]; (c)[20,56] https://doi.org/10.1371/journal.pone.0226544.t004 OA and climate change impacts on Atlantic Canadian fisheries PLOS ONE | https://doi.org/10.1371/journal.pone.0226544 January 10, 2020 19 / 29