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Oyster reef restoration supports increased nekton biomass and potential commercial fishery value

机译:牡蛎礁的恢复支持增加尼克顿生物量和潜在的商业渔业价值

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摘要

Across the globe, discussions centered on the value of nature drive many conservation and restoration decisions. As a result, justification for management activities increasingly asks for two lines of evidence: (1) biological proof of augmented ecosystem function or service, and (2) monetary valuation of these services. For oyster reefs, which have seen significant global declines and increasing restoration work, the need to provide both biological and monetary evidence of reef services on a local-level has become more critical in a time of declining resources. Here, we quantified species biomass and potential commercial value of nekton collected from restored oyster (Crassostrea virginica) reefs in coastal Louisiana over a 3-year period, providing multiple snapshots of biomass support over time. Overall, and with little change over time, fish and invertebrate biomass is 212% greater at restored oyster reefs than mud-bottom, or 0.12 kg m−2. The additional biomass of commercial species is equivalent to an increase of local fisheries value by 226%, or $0.09 m−2. Understanding the ecosystem value of restoration projects, and how they interact with regional management priorities, is critical to inform local decision-making and provide testable predictions. Quantitative estimates of potential commercial fisheries enhancement by oyster reef restoration such as this one can be used directly by local managers to determine the expected return on investment.
机译:在全球范围内,围绕自然价值的讨论推动了许多保护和恢复决策。结果,管理活动的理由越来越多地要求两类证据:(1)增强的生态系统功能或服务的生物学证据,以及(2)这些服务的货币价值。对于牡蛎礁来说,在全球范围内珊瑚礁数量大幅度减少,修复工作不断增加,在资源减少的时代,提供生物和金钱证据在当地一级进行服务的需求变得越来越重要。在这里,我们量化了三年时间内从路易斯安那州沿海地区的牡蛎礁(Crassostrea virginica)恢复的珊瑚中收集的物种生物量和潜在的商业价值,提供了一段时间内生物量支持的多个快照。总体而言,随着时间的推移,鱼类和无脊椎动物的生物量在恢复的牡蛎礁上比泥底高出212%,即0.12 kg m -2 。商业物种的额外生物量相当于当地渔业价值增加226%,即$ 0.09 m -2 。了解恢复项目的生态系统价值以及它们与区域管理优先级之间的相互作用,对于为当地决策提供依据并提供可检验的预测至关重要。牡蛎礁修复等可能增加商业渔业捕捞的定量估计值,地方管理人员可以直接使用它来确定预期的投资回报率。

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