Running head: Age- and size-structured oyster IPM

13 Structured population models, particularly sizeor age-structured, have a long history of 14 informing conservation and natural resource management. While size is often easier to measure 15 than age, and is the focus of many management strategies, age-structure can have important 16 effects on population dynamics that are not captured in size-only models. However, relatively few 17 studies have included the simultaneous effects of both ageand size-structure. To better 18 understand how population structure, particularly that of age and size, impacts restoration and 19 management decisions, we developed and compared a size-structured integral projection model 20 (IPM) and an ageand size-structured IPM, using a population of Crassostrea gigas oysters in the 21 northeastern Pacific Ocean. We analyzed sensitivity of model results across values of local 22 retention that give populations decreasing in size to populations increasing in size. We found that 23 ageand size-structured models yielded the best fit to the demographic data and provided more 24 reliable results about long-term demography. Elasticity analysis showed that population growth 25 rate was most sensitive to changes in the survival of both large (> 175 mm shell length) and small 26 (< 75 mm shell length) oysters, indicating that a maximum size limit, in addition to a minimum 27 size limit, could be an effective strategy for maintaining a sustainable population. In contrast, the 28 purely size-structured model did not detect the importance of large individuals. Finally, patterns 29 in stable age and stable size distributions differed between populations decreasing in size due to 30 limited local retention, and populations increasing in size due to high local retention. These 31 patterns can be used to determine population status and restoration success. The methodology 32 described here provides general insight into the necessity of including both ageand 33 size-structure into modeling frameworks when using population models to inform restoration and 34 management decisions. 35