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Incentivized debt conversion is a financing mechanism that can assist countries with a heavy debt burden to bolster their long-term domestic investment in nature conservation. The Nature Conservancy, an international conservation-based nongovernmental organization, is adapting debt conversions to support marine conservation efforts by small island developing states and coastal countries. Prioritizing debt conversion opportunities according to their potential return on investment can increase the impact and effectiveness of this finance mechanism. We developed guidance on how to do so with a decision-support approach that relies on a novel threat-based adaptation of cost-effectiveness analysis. We constructed scenarios by varying parameters of the approach, including enabling conditions, expected benefits, and threat classifications. Incorporating both abatable and unabatable threats affected priorities across planning scenarios. Similarly, differences in scenario construction resulted in unique solution sets for top priorities. We show how environmental organizations, private entities, and investment banks can adopt structured prioritization frameworks for making decisions about conservation finance investments, such as debt conversions. Our guidance can accommodate a suite of social, ecological, and economic considerations, making the approach broadly applicable to other conservation finance mechanisms or investment strategies that seek to establish a transparent process for return-on-investment decision-making., (© 2020 Society for Conservation Biology.)

Conservation scientists increasingly recognize that incorporating human values into conservation planning increases the chances for success by garnering broader project acceptance. However, methods for defining quantitative targets for the spatial representation of human well-being priorities are less developed. In this study we employ an approach for identifying regionally important human values and establishing specific spatial targets for their representation based on stakeholder outreach. Our primary objective was to develop a spatially-explicit conservation plan that identifies the most efficient locations for conservation actions to meet ecological goals while sustaining or enhancing human well-being values within the coastal and nearshore areas of the western Lake Erie basin (WLEB). We conducted an optimization analysis using 26 features representing ecological and human well-being priorities (13 of each), and included seven cost layers. The influence that including human well-being had on project results was tested by running five scenarios and setting targets for human well-being at different levels in each scenario. The most important areas for conservation to achieve multiple goals are clustered along the coast, reflecting a concentration of existing or potentially restorable coastal wetlands, coastal landbird stopover habitat and terrestrial biodiversity, as well as important recreational activities. Inland important areas tended to cluster around trails and high quality inland landbird stopover habitat. Most concentrated areas of importance also are centered on lands that are already conserved, reflecting the lower costs and higher benefits of enlarging these conserved areas rather than conserving isolated, dispersed areas. Including human well-being features in the analysis only influenced the solution at the highest target levels.

Pelagic ecosystems support a significant and vital component of the ocean's productivity and biodiversity. They are also heavily exploited and, as a result, are the focus of numerous spatial planning initiatives. Over the past decade, there has been increasing enthusiasm for protected areas as a tool for pelagic conservation, however, few have been implemented. Here we demonstrate an approach to plan protected areas that address the physical and biological dynamics typical of the pelagic realm. Specifically, we provide an example of an approach to planning protected areas that integrates pelagic and benthic conservation in the southern Benguela and Agulhas Bank ecosystems off South Africa. Our aim was to represent species of importance to fisheries and species of conservation concern within protected areas. In addition to representation, we ensured that protected areas were designed to consider pelagic dynamics, characterized from time-series data on key oceanographic processes, together with data on the abundance of small pelagic fishes. We found that, to have the highest likelihood of reaching conservation targets, protected area selection should be based on time-specific data rather than data averaged across time. More generally, we argue that innovative methods are needed to conserve ephemeral and dynamic pelagic biodiversity.

The ratification of the United Nations High Seas Treaty will help protect overlooked oceanic ecosystems, leading to an expected large increase in the declaration of oceanic (defined here as waters >200 m in depth) Marine Protected Areas (oMPAs) in the current decade. In many places this will need to be done in cooperation with existing sectoral management bodies. Despite this likely expansion, our current understanding of the ecological benefits of oMPAs is derived primarily from coastal protected areas, which are shallower, generally well mixed, and face different threats than oMPAs. Consequently, the strong scientific consensus for the ecological benefits of coastal MPAs is lacking for oMPAs. Emerging new sampling platforms and methods can help address this gap and inform the design and placement of new oMPAs that aim to conserve both pelagic and benthic biodiversity. Oceans beyond the continental shelf represent the largest yet least protected environments. The new agreement to increase protection targets to 30% by 2030 and the recent United Nations (UN) High Seas Treaty try to address this gap, and an increase in the declaration of oceanic Marine Protected Areas (oMPAs) in waters beyond 200 m in depth is likely. Here we find that there is contradictory evidence concerning the benefits of oMPAs in terms of protecting pelagic habitats, providing refuge for highly mobile species, and potential fisheries benefits. We discover a mismatch between oMPA management objectives focusing on protection of pelagic habitats and biodiversity, and scientific research focusing on fisheries benefits. We suggest that the solution is to harness emerging technologies to monitor inside and outside oMPAs. [ABSTRACT FROM AUTHOR]

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Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Convention on Biological Diversity requires that member nations establish protected area networks that are representative of the country's biodiversity. The identification of priority sites to achieve outstanding representation targets is typically accomplished through formal conservation assessments. However, representation in conservation assessments or gap analyses has largely been interpreted based on a static view of biodiversity. In a rapidly changing climate, the speed of changes in biodiversity distribution and abundance is causing us to rethink the viability of this approach. Here we describe three explicit strategies for climate change adaptation as part of national conservation assessments: conserving the geophysical stage, identifying and protecting climate refugia, and promoting cross-environment connectivity. We demonstrate how these three approaches were integrated into a national terrestrial conservation assessment for Papua New Guinea, one of the most biodiverse countries on earth. Protected areas identified based on representing geophysical diversity were able to capture over 90% of the diversity in vegetation communities, suggesting they could help protect representative biodiversity regardless of changes in the distribution of species and communities. By including climate change refugia as part of the national conservation assessment, it was possible to substantially reduce the amount of environmental change expected to be experienced within protected areas, without increasing the overall cost of the protected area network. Explicitly considering environmental heterogeneity between adjacent areas resulted in protected area networks with over 40% more internal environmental connectivity. These three climate change adaptation strategies represent defensible ways to guide national conservation priority given the uncertainty that currently exists in our ability to predict climate changes and their impacts. Importantly, they are also consistent with data and expertise typically available during national conservation assessments, including in developing nations. This means that in the vast majority of countries, these strategies could be implemented immediately. [ABSTRACT FROM AUTHOR]

Conservation decisions often involve uncertainty about the underlying ecological and social systems and, in particular, how these systems will respond to the implementation of conservation actions. Future decision making can be improved by learning more about these systems and their responses to past conservation actions, by evaluating the performance of the actions being undertaken. This is a "passive" adaptive management approach to conservation. However, the purposeful and experimental application of different conservation actions can yield greater knowledge through more rapid and targeted learning. This is an "active" adaptive management approach to conservation. Improving future management decisions through learning should be viewed as essential to all conservation plans. Unfortunately, the incorporation of explicit learning processes within the greater framework of conservation planning processes is rare. Here, we provide an overview of factors to consider when attempting the implementation of an adaptive approach to conservation planning, along with ideas for future research. [ABSTRACT FROM AUTHOR]

Land acquisition is a common approach to biodiversity conservation but is typically subject to property availability on the public market. Consequently, conservation plans are often unable to be implemented as intended. When properties come on the market, conservation agencies must make a choice: purchase immediately, often without a detailed knowledge of its biodiversity value; survey the parcel and accept the risk that it may be removed from the market during this process; or not purchase and hope a better parcel comes on the market at a later date. We describe both an optimal method, using stochastic dynamic programming, and a simple rule of thumb for making such decisions. The solutions to this problem illustrate how optimal conservation is necessarily dynamic and requires explicit consideration of both the time period allowed for implementation and the availability of properties. [ABSTRACT FROM AUTHOR]

Highlights: [•] Ecoregional priorities were identified using biodiversity, habitat, and management criteria. [•] Intersecting terrestrial, freshwater, and marine priorities identified global priorities. [•] Return-on-investment principles were useful to evaluate these global conservation priorities. [•] More data on strategy costs could help increase the use of return- on-investment in conservation. [ABSTRACT FROM AUTHOR]

The gross under-resourcing of conservation endeavours has placed an increasing emphasis on spending accountability. Increased accountability has led to monitoring forming a central element of conservation programs. Although there is little doubt that information obtained from monitoring can improve management of biodiversity, the cost (in time and/or money) of gaining this knowledge is rarely considered when making decisions about allocation of resources to monitoring. We present a simple framework allowing managers and policy advisors to make decisions about when to invest in monitoring to improve management. [Copyright &y& Elsevier]