We dedicate this paper to Dr. Fred Conte, California state Aquaculture Specialist Emeriti of UC Davis
Cooperative Extension, who sadly passed in 2021. We thank him posthumously for his deep insight and
guidance surrounding oyster #aquaculture in the state (10/10). And thank you Sea Grant!!
Interestingly, growth was 17x faster in the 1950s compared to the increases after 1980, which we hypothesize maybe due to the proliferation (at the same time as the major fishery shock)of regulations in the state (and nation); a ~2:1 restrictive to enabling policy landscape that emerged (6/10)
Halley E. Froehlich
Halley E. Froehlich
Last, but certainly not least, we collected #oyster data going back to 1888 & found more evidence for blue transitions. More specifically, that a 'full blue transition' occurred (no fishing, only farming) sometime in the mid-1930s. But it's hard to say exactly when bc the data were misreported(8/10)
In all, we found when dramatic, sudden declines occur in wild capture we consistently saw some level of evidence of aquaculture emergence or growth within a 5 year window of time. With variability of food systems projected to increase with time this has important implications for #aquaculture (9/10)
Why/how would shocks of wild capture influence #aquaculture you ask? Humans are largely reactive, & there is plenty of qualitative examples of things like hatchery interventions, retraining programs, & policies that promote the emergence & growth of aquaculture when wild stocks rapidly decline(3/10)
Aggregating (A LOT OF) different time series of wild and farmed production, we found several shocks (sudden & sig. decline), but the biggest was in 1984 when N. anchovy and yellowfin both collapsed (the red line) (4/10)
Overlapping with that 1984 wild shock time period we found a 'breakpoint' in aquaculture growth (dominated by mollusks not fish), with a complete change in average directionality (growth specifically). Importantly this held with a longer, though more uncertain time series (5/10)
1st we expanded the basic theory based on parallel systems and shock dynamics, hypothesizing that major shocks to wild fisheries (volume & value) may be more likely to influence aquaculture and spur blue transitions, especially short term. Importantly, it doesn't have to be the same species (2/10)
Excited to share our new OA paper exploring the scales and quantitative drivers of 'blue transitions' (aka fishing🎣 ➡️ aquatic farming🌊🚜) using California as a case study #aquaculture (1/10) iopscience.iop.org/article/10.1...
That said, incorporating policy effects into a quantitative model is challenging and the number of policies did not improve our predictive model of aquaculture production. What did was CA population, US GDP, and wild catch CV (as we hypothesized!) (7/10)
