Résumé: The eastern oyster once provided major societal and ecosystem benefits, but these benefits have been threatened in recent decades by large declines in oyster harvests. In many areas, recovery of oyster aquaculture faces significant societal opposition and spatial constraints limiting its ability to meet expectations regarding future food needs and provision of ecosystem services. In Virginia, oyster aquaculture has begun to expand, concurrent with an increase in subaqueous leased areas (over 130,000 acres of grounds are currently leased). Though private leases must in theory be used for oyster production, in practice, they can be held for other reasons, such as speculation or intentional exclusion of others. These factors have led to large variation over time and space in the use of leases in lower Chesapeake Bay; and privately leased grounds are now thought to be underutilized for oyster production. This research examined potential barriers to expansion of oyster aquaculture in Virginia. We first evaluated if a lack of space was limiting industry expansion and quantified temporal and spatial trends in the use and productivity of leases. Then, differences in used and non-used leases were investigated in relation to variables thought to be related to “not in my backyard” attitudes, congestion, speculation, local economic and environmental conditions. Finally, the performance of the Virginia leasing system was compared with those in other states along the U.S. East and Gulf Coasts. We found limited evidence for spatial constraints on aquaculture leasing, but strong evidence for social and regulatory inefficiencies. Although rates of lease use increased from 2006 to 2016, only 33% of leases were ever used for oyster production and about 63% of leaseholders reported no commercial harvests. Non-used leases tended to be smaller, and were found in more populated, high-income regions, consistent with both speculative and exclusionary uses. Virginia had the second lowest level of total production of cultured oysters per leased acre among the states on the East and Gulf Coasts of the United States. These results indicate that there is room for oyster aquaculture expansion in Virginia if societal, regulatory, and economic barriers can be reduced or if existing leased areas are used more efficiently.

Résumé: Aim Cetaceans are inherently difficult to study due to their elusive, pelagic and often highly migratory nature. New Zealand waters are home to 50% of the world's cetacean species, but their spatial distributions are poorly known. Here, we model distributions of 30 cetacean taxa using an extensive at-sea sightings dataset (n > 14,000) and high-resolution (1 km2) environmental data layers. Location New Zealand's Exclusive Economic Zone (EEZ). Methods Two models were used to predict probability of species occurrence based on available sightings records. For taxa with <50 sightings (n = 15), Relative Environmental Suitability (RES), and for taxa with ≥50 sightings (n = 15), Boosted Regression Tree (BRT) models were used. Independently collected presence/absence data were used for further model evaluation for a subset of taxa. Results RES models for rarely sighted species showed reasonable fits to available sightings and stranding data based on literature and expert knowledge on the species' autecology. BRT models showed high predictive power for commonly sighted species (AUC: 0.79–0.99). Important variables for predicting the occurrence of cetacean taxa were temperature residuals, bathymetry, distance to the 500 m isobath, mixed layer depth and water turbidity. Cetacean distribution patterns varied from highly localised, nearshore (e.g., Hector's dolphin), to more ubiquitous (e.g., common dolphin) to primarily offshore species (e.g., blue whale). Cetacean richness based on stacked species occurrence layers illustrated patterns of fewer inshore taxa with localised richness hotspots, and higher offshore richness especially in locales of the Macquarie Ridge, Bounty Trough and Chatham Rise. Main conclusions Predicted spatial distributions fill a major knowledge gap towards informing future assessments and conservation planning for cetaceans in New Zealand's extensive EEZ. While sightings datasets were not spatially comprehensive for any taxa, these two best available approaches allow for predictive modelling of both more common, and of rarely sighted, cetacean species with limited available information.