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Biodiversity offsetting is widely used to offset negative impacts of development on biodiversity. However, offsets can affect the distribution of benefits among beneficiaries, due to the redistribution of ecosystem services caused by impacts and offsets. Here, we compared the distribution of fishery economic benefits and losses to commercial and recreational fishers under two different offset policy rules: offset locations in close proximity to impact sites, and spatially unrestricted offsetting. With a focus on mangrove and seagrass ecosystems in Queensland, Australia, we measured how the distribution of net outcomes would change using the Gini coefficient. Different offset policy rules had similar effects on the redistribution of fishery benefits among commercial and recreational fishers. However, both offset policy rules failed to fully compensate for losses of fishery benefits for most affected beneficiaries. Locating offsets in close proximity to impact sites achieved slightly more evenly-distributed benefits among recreational fishers and among most types of commercial fishers. The findings suggest that in this system, even though the distribution of net outcomes of impact-offset projects for fishers are somewhat evenly distributed, they tend to be uniformly negative for both recreational and commercial fishers. • Fish habitat offsets in Queensland fails to fully offset losses of fishery benefits for all affected fishery beneficiaries. • Different offset policy rules had similar effects on the redistribution of ecosystem services among beneficiaries. • Offsets generating more even distribution of benefits among beneficiaries may yield smaller ecological gains than losses. [ABSTRACT FROM AUTHOR]

1. Protected areas often need to provide recreational opportunities whilst conserving biodiversity. Recreation brings important benefits to human well-being, and allowing people to experience nature in protected areas can also provide revenue and support for conservation objectives. However, not all recreational activities are compatible with environmental management goals. 2. Here, we show how a coastal protected area can be zoned to satisfy both recreational and conservation objectives. 3. We collected empirical data on the effect of recreational disturbance to foraging shorebirds in Moreton Bay Marine Park, Queensland, Australia, and calculated the benefit of alternative protected area zone types on shorebird representation using a zero-inflated negative binomial model. The predictions from this model were used to optimize a zoning plan in a linear programming framework that balances recreational use with shorebird conservation. Costs reflect foregone recreational opportunity, thereby facilitating solutions that minimize restrictions on recreational use of the coastline. 4. We discover a consistent negative effect of recreational use of the foreshore on shorebird occupancy and abundance and show that, despite this, zoning can be used to achieve shorebird representation targets with only a small cost to recreational opportunity. 5. When dog recreation is permitted at all sites, a 91% shorebird representation target can be met, indicating that de facto patterns of recreation were rather well segregated from areas used by shorebirds. By restricting dog recreation to five sites and allowing people to access all other foreshore sites, shorebird representation increased to 97%. 6. Synthesis and applications. Our approach of calculating the contribution of each zone type towards conservation objectives results in zoning plans with robust estimates of conservation benefit that can be readily implemented by managers. Specifically, we estimated the effects of removing people and domestic dog recreation within each intertidal site on shorebird abundance to inform coastal zoning plans. Incorporating cost as foregone recreational opportunity results in zoning plans that minimize the number of people required to make a behavioural change. Compliance to zone types is often ultimately voluntary so integrating the current intensity of recreational use is more likely to generate workable zoning plans. [ABSTRACT FROM AUTHOR]

Spatially explicit information on the financial costs of conservation actions can improve the ability of conservation planning to achieve ecological and economic objectives, but the magnitude of this improvement may depend on the accuracy of the cost estimates. Data on costs of conservation actions are inherently uncertain. For example, the cost of purchasing a property for addition to a protected-area network depends on the individual landholder's preferences, values, and aspirations, all of which vary in space and time, and the effect of this uncertainty on the conservation priority of a site is relatively untested. We investigated the sensitivity of the conservation priority of sites to uncertainty in cost estimates. We explored scenarios for expanding (four-fold) the protected-area network in Queensland, Australia to represent a range of vegetation types, species, and abiotic environments, while minimizing the cost of purchasing new properties. We estimated property costs for 17, 790 10 × 10 km sites with data on unimproved land values. We systematically changed property costs and noted how these changes affected conservation priority of a site. The sensitivity of the priority of a site to changes in cost data was largely dependent on a site's importance for meeting conservation targets. Sites that were essential or unimportant for meeting targets maintained high or low priorities, respectively, regardless of cost estimates. Sites of intermediate conservation priority were sensitive to property costs and represented the best option for efficiency gains, especially if they could be purchased at a lower price than anticipated. Thus, uncertainty in cost estimates did not impede the use of cost data in conservation planning, and information on the sensitivity of the conservation priority of a site to estimates of the price of land can be used to inform strategic conservation planning before the actual price of the land is known., (© 2010 University of Queensland. Journal compilation © 2010 Society for Conservation Biology.)