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Reassembling ecological communities and rebuilding habitats through active restoration treatments require curating the selection of plant species to use in seeding and planting mixes. Ideally, these mixes should be assembled based on attributes that support ecosystem function and services, promote plant and animal species interactions and ecological networks in restoration while balancing project constraints. Despite these critical considerations, it is common for species mixes to be selected opportunistically. Reframing the selection of seed mixes for restoration around ecological objectives is essential for success but accessible methods and tools are needed to support this effort. We developed a framework to optimize species seed mixes based on prioritizing plant species attributes to best support different objectives for ecosystem functions, services and trophic relationships such as pollination, seed dispersal and herbivory. We compared results to approaches where plant species are selected to represent plant taxonomic richness, dominant species and at random. We tested our framework in European alpine grasslands by identifying 176 plant species characteristic of the species pool, and identified 163 associated attributes affiliated to trophic relationships, ecosystem functions and services. In all cases, trophic relationships, ecosystem functions and services can be captured more efficiently through objective-based prioritization using the functional identity of plant species. Solutions (plant species lists) can be compared quantitatively, in terms of costs, species or objectives. We confirm that a random draw of plant species from the regional plant species pool cannot be assumed to support other trophic groups and ecosystem functions and services. Synthesis and Applications. Our framework is presented as a proof-of-concept to help restoration practitioners better apply quantitative decision support to plant species selection to efficiently meet ecological restoration outcomes. Our approach may be tailored to any restoration initiative, habitat or restoration targets where seeding or planting mixes will be applied in active treatments. As global priority and resources are increasingly placed into restoration, this approach could be advanced to help make efficient decisions for many stages of the restoration process.

The ocean contains unique biodiversity, provides valuable food resources and is a major sink for anthropogenic carbon. Marine protected areas (MPAs) are an effective tool for restoring ocean biodiversity and ecosystem services1,2, but at present only 2.7% of the ocean is highly protected3. This low level of ocean protection is due largely to conflicts with fisheries and other extractive uses. To address this issue, here we developed a conservation planning framework to prioritize highly protected MPAs in places that would result in multiple benefits today and in the future. We find that a substantial increase in ocean protection could have triple benefits, by protecting biodiversity, boosting the yield of fisheries and securing marine carbon stocks that are at risk from human activities. Our results show that most coastal nations contain priority areas that can contribute substantially to achieving these three objectives of biodiversity protection, food provision and carbon storage. A globally coordinated effort could be nearly twice as efficient as uncoordinated, national-level conservation planning. Our flexible prioritization framework could help to inform both national marine spatial plans4 and global targets for marine conservation, food security and climate action. Using a globally coordinated strategic conservation framework to plan an increase in ocean protection through marine protected areas can yield benefits for biodiversity, food provisioning and carbon storage.

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., Article Impact Statement: Prioritizations that explicitly incorporate abatable and unabatable threats can improve conservation return on investment decision‐making.

1. Globally, protected areas are being established to protect biodiversity and to promote ecosystem resilience. The typical spatial conservation planning process leading to the creation of these protected areas focuses on representation and replication of ecological features, often using decision support tools such as Marxan. Yet, despite the important role ecological connectivity has in metapopulation persistence and resilience, Marxan currently requires manual input or specialized scripts to explicitly consider connectivity. 2. ‘Marxan Connect’ is a new open source, open access Graphical User Interface (GUI) tool designed to assist conservation planners with the appropriate use of data on ecological connectivity in protected area network planning. 3. Marxan Connect can facilitate the use of estimates of demographic connectivity (e.g. derived from animal tracking data, dispersal models, or genetic tools) or structural landscape connectivity (e.g. isolation by resistance). This is accomplished by calculating metapopulation‐relevant connectivity metrics (e.g. eigenvector centrality) and treating those as conservation features or by including the connectivity data as a spatial dependency amongst sites in the prioritization process. 4. Marxan Connect allows a wide group of users to incorporate directional ecological connectivity into conservation planning with Marxan. The solutions provided by Marxan Connect, combined with ecologically relevant post‐hoc testing, are more likely to support persistent and resilient metapopulations (e.g. fish stocks) and provide better protection for biodiversity.

Innovation has the potential to enable conservation science and practice to keep pace with the escalating threats to global biodiversity, but this potential will only be realized if such innovations are designed and developed to fulfill specific needs and solve well-defined conservation problems. We propose that business-world strategies for assessing the practicality of innovation can be applied to assess the viability of innovations, such as new technology, for addressing biodiversity conservation challenges. Here, we outline a five-step, "lean start-up" based approach for considering conservation innovation from a business-planning perspective. Then, using three prominent conservation initiatives - Marxan (software), Conservation Drones (technology support), and Mataki (wildlife-tracking devices) - as case studies, we show how considering proposed initiatives from the perspective of a conceptual business model can support innovative technologies in achieving desired conservation outcomes.

Advancing technology represents an unprecedented opportunity to enhance our capacity to conserve the Earth's biodiversity. However, this great potential is failing to materialize and rarely endures. We contend that unleashing the power of technology for conservation requires an internationally coordinated strategy that connects the conservation community and policy-makers with technologists. We argue an international conservation technology entity could (1) provide vision and leadership, (2) coordinate and deliver key services necessary to ensure translation from innovation to effective deployment and use of technology for on-the-ground conservation across the planet, and (3) help integrate innovation into biodiversity conservation policy from local to global scales, providing tools to monitor outcomes of conservation action and progress towards national and international biodiversity targets. This proposed entity could take the shape of an international alliance of conservation institutions or a formal intergovernmental institution. Active and targeted uptake of emerging technology can help society achieve biodiversity conservation goals.

Spatial prioritization is a critical step in conservation planning, a process designed to ensure that limited resources are applied in ways that deliver the highest possible returns for biodiversity and human wellbeing. In practice, many spatial prioritizations fall short of their potential by focusing on places rather than actions, and by using data of snapshots of assets or threats rather than estimated impacts. We introduce spatial action mapping as an approach that overcomes these shortfalls. This approach produces a spatially explicit view of where and how much a given conservation action is likely to contribute to achieving stated conservation goals. Through seven case examples, we demonstrate simple to complex versions of how this method can be applied across local to global scales to inform decisions about a wide range of conservation actions and benefits. Spatial action mapping can support major improvements in efficient use of conservation resources and will reach its full potential as the quality of environmental, social, and economic datasets converge and conservation impact evaluations improve.

To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature’s contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions.

Conservation strategies based on charismatic flagship species, such as tigers, lions, and elephants, successfully attract funding from individuals and corporate donors. However, critics of this species-focused approach argue it wastes resources and often does not benefit broader biodiversity. If true, then the best way of raising conservation funds excludes the best way of spending it. Here we show that this conundrum can be resolved, and that the flagship species approach does not impede cost-effective conservation. Through a tailored prioritization approach, we identify places containing flagship species while also maximizing global biodiversity representation (based on 19,616 terrestrial and freshwater species). We then compare these results to scenarios that only maximized biodiversity representation, and demonstrate that our flagship-based approach achieves 79−89% of our objective. This provides strong evidence that prudently selected flagships can both raise funds for conservation and help target where these resources are best spent to conserve biodiversity., Conservation actions focused on flagship species are effective at raising funds and awareness. Here, McGowan et al. show that prioritizing areas for conservation based on the presence of flagship species results in the selection of areas with ~ 79-89% of the total species that would be selected by maximizing biodiversity representation only.

Global conservation targets (e.g. Aichi Target 11) have helped drive a dramatic expansion of the global protected area (PA) network. Credible metrics have an important role to play in evaluating and expanding PAs to achieve conservation outcomes and objectives. For metrics to be useful and adopted, they need to be transparent, easy to understand, and easy to implement. We present two complementary metrics, “mean protection gap” and “mean target achievement”, for evaluating representation target achievement in PA networks along with the R package “ConsTarget” that calculates and plots both metrics. We use Australia's proposed Commonwealth Marine Reserve network as a case study to demonstrate the application of these metrics. We recommend the metrics be used to evaluate the progress towards building representative PA networks in line with Aichi target 11's goals.

Effective conservation management interventions must combat threats and deliver benefits at costs that can be achieved within limited budgets. Considerable effort has focused on measuring the potential benefits of conservation interventions, but explicit quantification of the financial costs of implementation is rare. Even when costs have been quantified, haphazard and inconsistent reporting means published values are difficult to interpret. This reporting deficiency hinders progress toward a collective understanding of the financial costs of management interventions across projects and thus limits the ability to identify efficient solutions to conservation problems or attract adequate funding. We devised a standardized approach to describing financial costs reported for conservation interventions. The standards call for researchers and practitioners to describe the objective and outcome, context and methods, and scale of costed interventions and to state which categories of costs are included and the currency and date for reported costs. These standards aim to provide enough contextual information that readers and future users can interpret the cost data appropriately. We suggest these standards be adopted by major conservation organizations, conservation science institutions, and journals so that cost reporting is comparable among studies. This would support shared learning and enhance the ability to identify and perform cost‐effective conservation.

Aim To assess the efficacy of marine reserves in Australia for shy albatross, using long‐term tracking data. Location Albatross Island, Tasmania, and south Australian waters. Methods We integrated a tracking dataset consisting of 111 individuals collected over 23 years and generated Brownian bridge kernel density estimations to identify important habitat. We quantified the overlap between the foraging distribution of early incubating adults and post‐fledgling juveniles with management boundaries and marine reserves. We compared the extent of coverage of albatross foraging areas by Marine Protection Areas (MPAs) relative to a randomly designed network of the same size to determine whether the spatial protection measures are likely to be effective. Results Incubating adults consistently foraged in waters to the northwest of Tasmania while post‐fledglings occupied shelf waters around Tasmania and South Australia. We show that our sample of 99 incubating adults adequately represented the population but that our sample of 12 post‐fledgling birds was insufficient, thereby limiting the confidence in our results for this life stage. The Commonwealth Government has the majority of management responsibility for shy albatross at‐sea, containing 88% and 90% of the area occupied most intensively by adult and post‐fledgling shy albatross, respectively. Randomly designed reserve networks outperformed the current MPA network for both life stages, such that the mean protection by a random reserve system was 30% and 12% higher than the actual protection for adults and juveniles in Commonwealth waters. Main conclusions Important foraging habitat of shy albatross from Albatross Island is mostly within Commonwealth‐managed waters. The current MPA network, the only spatial protection measure for shy albatross, provides less coverage for this species than a randomly placed network. An increase in the representation of productive shelf waters in MPA networks would benefit the conservation of shy albatross through reducing fisheries interactions and protecting habitat in these regions.

The Adriatic and Ionian Region is an important area for both strategic maritime development and biodiversity conservation in the European Union (EU). However, given that both EU and non-EU countries border the sea, multiple legal and regulatory frameworks operate at different scales, which can hinder the coordinated long-term sustainable development of the region. Transboundary marine spatial planning can help overcome these challenges by building consensus on planning objectives and making the trade-offs between biodiversity conservation and its influence on economically important sectors more explicit. We address this challenge by developing and testing 4 spatial prioritization strategies with the decision-support tool Marxan, which meets targets for biodiversity conservation while minimizing impacts to users. We evaluated these strategies in terms of how priority areas shift under different scales of target setting (e.g., regional vs. country level). We also examined the trade-off between cost-efficiency and how equally solutions represent countries and maritime industries (n = 14) operating in the region with the protection-equality metric. We found negligible differences in where priority conservation areas were located when we set targets for biodiversity at the regional versus country scale. Conversely, the prospective impacts on industries, when considered as costs to be minimized, were highly divergent across scenarios and biased the placement of protection toward industries located in isolation or where there were few other industries. We recommend underpinning future marine spatial planning efforts in the region through identification of areas of national significance, transboundary areas requiring cooperation between countries, and areas where impacts on maritime industries require careful consideration of the trade-off between biodiversity conservation and socioeconomic objectives.

Summary paragraphTo meet the ambitious objectives of biodiversity and climate conventions, countries and the international community require clarity on how these objectives can be operationalized spatially, and multiple targets be pursued concurrently1. To support governments and political conventions, spatial guidance is needed to identify which areas should be managed for conservation to generate the greatest synergies between biodiversity and nature’s contribution to people (NCP). Here we present results from a joint optimization that maximizes improvements in species conservation status, carbon retention and water provisioning and rank terrestrial conservation priorities globally. We found that, selecting the top-ranked 30% (respectively 50%) of areas would conserve 62.4% (86.8%) of the estimated total carbon stock and 67.8% (90.7%) of all clean water provisioning, in addition to improving the conservation status for 69.7% (83.8%) of all species considered. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to improve the conservation status of 86.3% of plant and vertebrate species on Earth. Our results provide a global baseline on where land could be managed for conservation. We discuss how such a spatial prioritisation framework can support the implementation of the biodiversity and climate conventions.

International audience; Climate change threatens Earth's biodiversity, although its impacts are variable and depend on the capacity of species and ecosystems to cope with the magnitude and speed of change. Natural protected areas (NPAs) constitute potential refugia for species' persistence and for sustaining the provisioning of ecosystem services. Biosphere reserves are NPAs that are less altered by human actions and provide habitat to endemic, threatened or endangered species. Here, we aim to evaluate the threat imposed by climate change on the network of biosphere reserves in Mexico. Focusing on five bioclimatic variables, we computed the climatic space – measured as an n-dimensional hypervolume – of 40 NPAs. Increases in temperature are predicted for all NPAs by 2050, whereas decreases in annual rainfall are predicted for 30 NPAs. By 2050, 31 NPAs that provide habitat to 22,866 recorded species are predicted to lose 100% of their baseline climatic space, shifting to completely novel climates. On average, the other nine NPAs are predicted to lose 55.7% (SD = 26.7%) of their baseline climatic space, while 54.5% (SD = 32.5%) of the future climatic space will be novel. Seventeen NPAs may lose climate variability (homogenization), decreasing species' niches. The extent to which non-analogue conditions will remain within the tolerance of species and ecosystems is currently unknown. Finally, we propose a vulnerability index to categorise NPAs based on their loss of existing climatic space, total geographic area, species richness, and uniqueness of species composition, finding los Tuxtlas and Tiburon Ballena as the most and least vulnerable NPAs, respectively.

We evaluate the extent of climate change adaptation in the global protected seascape, and identify ways to further advance it., The impacts of climate change and the socioecological challenges they present are ubiquitous and increasingly severe. Practical efforts to operationalize climate-responsive design and management in the global network of marine protected areas (MPAs) are required to ensure long-term effectiveness for safeguarding marine biodiversity and ecosystem services. Here, we review progress in integrating climate change adaptation into MPA design and management and provide eight recommendations to expedite this process. Climate-smart management objectives should become the default for all protected areas, and made into an explicit international policy target. Furthermore, incentives to use more dynamic management tools would increase the climate change responsiveness of the MPA network as a whole. Given ongoing negotiations on international conservation targets, now is the ideal time to proactively reform management of the global seascape for the dynamic climate-biodiversity reality.

Systematic conservation planning and Key Biodiversity Areas (KBAs) are the two most widely used approaches for identifying important sites for biodiversity. However, there is limited advice for conservation policy makers and practitioners on when and how they should be combined. Here we provide such guidance, using insights from the recently developed Global Standard for the Identification of KBAs and the language of decision science to review and clarify their similarities and differences. We argue the two approaches are broadly similar, with both setting transparent environmental objectives and specifying actions. There is however greater contrast in the data used and actions involved, as the KBA approach uses biodiversity data alone and identifies sites for monitoring and vigilance actions at a minimum, whereas systematic conservation planning combines biodiversity and implementation-relevant data to guide management actions. This difference means there is much scope for combining approaches, so conservation planners should use KBA data in their analyses, setting context-specific targets for each KBA type, and planners and donors should use systematic conservation planning techniques when prioritizing between KBAs for management action. In doing so, they will benefit conservation policy, practice and research by building on the collaborations formed through the KBA Standard's development.

Aim Mega-diverse coral reef ecosystems are declining globally, necessitating conservation prioritizations to protect biodiversity and ecosystem services of sites with high functional integrity to promote persistence. In practice however, the design of marine-protected area (MPA) systems often relies on broad classifications of habitat class and size, making the tacit assumption that all reefs are of comparable condition. We explored the impact of this assumption through a novel, pragmatic approach for incorporating variability in coral cover in a large-scale regional spatial prioritization plan. Location The Coral Triangle. Methods We developed a spatially explicit predictive model of hard coral cover based on freely available macro-ecological data to generate a complete regional map of coral cover as a proxy for reef condition. We then incorporate this information in spatial conservation prioritization software Marxan to design an MPA system that meets specific conservation objectives. Results We discover prioritizations using area-based representation of reef habitat alone may overestimate the conservation benefit, defined as the amount of hard coral cover protected, by up to 64%. We find substantial differences in conservation priorities and an overall increase in habitat quality metrics when accounting for predicted coral cover. Main conclusions This study shows that including habitat condition in a large-scale marine spatial prioritization is feasible within time and resource constraints, and calls for increased implementation, and evaluation, of such ecologically relevant planning approaches to enhance potential conservation effectiveness.

Representation of ecosystems in protected area networks and conservation strategies is a core principle of global conservation priority setting approaches and a commitment in Aichi Target 11 of the Convention on Biological Diversity. The 2030 Sustainable Development Goals (SDGs) explicitly call for the conservation of terrestrial, freshwater, and marine ecosystems. Accurate ecosystem distribution maps are required to assess representation of ecosystems in protected areas, but standardized, high spatial resolution, and globally comprehensive ecosystem maps have heretofore been lacking. While macroscale global ecoregions maps have been used in global conservation priority setting exercises, they do not identify distinct localized ecosystems at the occurrence (patch) level, and instead describe large ecologically meaningful areas within which additional conservation planning and management are necessary. We describe a new set of maps of globally consistent climate regions and ecosystems at a much finer spatial resolution (250 m) than existing ecological regionalizations. We then describe a global gap analysis of the representation of these ecosystems in protected areas. The new map of terrestrial World Ecosystems was derived from the objective development and integration of 1) global temperature domains, 2) global moisture domains, 3) global landforms, and 4) 2015 global vegetation and land use. These new terrestrial World Ecosystems do not include either freshwater or marine ecosystems, but analog products for the freshwater and marine domains are in development. A total of 431 World Ecosystems were identified, and of these a total of 278 units were natural or semi-natural vegetation/environment combinations, including different kinds of forestlands, shrublands, grasslands, bare areas, and ice/snow regions. The remaining classes were different kinds of croplands and settlements. Of the 278 natural and semi-natural classes, 9 were not represented in global protected areas with a strict biodiversity conservation management objective (IUCN management categories I-IV), and an additional 206 were less than 8.5% protected (half way to the 17% Aichi Target 11 goal). Forty four classes were between 8.5% and 17% protected (more than half way towards the Aichi 17% target), and only 19 classes exceeded the 17% Aichi target. However, when all protected areas (IUCN management categories I-VI plus protected areas with no IUCN designation) were included in a separate global gap analysis, representation of ecosystems increases substantially, with a third of the ecosystems exceeding the 17% Aichi target, and another third between 8.5% and 17%. The overall protection (representation) of global ecosystems in protected areas is considerably less when assessed using only strictly conserved protected areas, and more if all protected areas are included in the analysis. Protected area effectiveness should be included in further evaluations of global ecosystem protection. The ecosystems with the highest representation in protected areas were often bare or sparsely vegetated and found in inhospitable environments (e.g. cold mountains, deserts), and the eight most protected ecosystems were all snow and ice ecosystems. In addition to the global gap analysis of World Ecosystems in protected areas, we report on the representation results for the ecosystems in each biogeographic realm (Neotropical, Nearctic, Afrotropical, Palearctic, Indomalayan, Australasian, and Oceania).

Tun Mustapha Park, in Sabah, Malaysia, was gazetted in May 2016 and is the first multiple-use park in Malaysia where conservation, sustainable resource use and development co-occur within one management framework. We applied a systematic conservation planning tool, Marxan with Zones, and stakeholder consultation to design and revise the draft zoning plan. This process was facilitated by Sabah Parks, a government agency, and WWF-Malaysia, under the guidance of the Tun Mustapha Park steering committee and with support from the University of Queensland. Four conservation and fishing zones, including no-take areas, were developed, each with representation and replication targets for key marine habitats, and a range of socio-economic and community objectives. Here we report on how decision-support tools informed the reserve design process in three planning stages: prioritization, government review, and community consultation. Using marine habitat and species representation as a reporting metric, we describe how the zoning plan changed at each stage of the design process. We found that the changes made to the zoning plan by the government and stakeholders resulted in plans that compromised the achievement of conservation targets because no-take areas were moved away from villages and the coastline, where unique habitats are located. The design process highlights a number of lessons learned for future conservation zoning, which we believe will be useful as many other places embark on similar zoning processes on land and in the sea.

Marine protected areas (MPAs) form the cornerstone of marine conservation. Identifying which factors contribute to their success or failure is crucial considering the international conservation targets for 2020 and the limited funds generally available for marine conservation. We identified common factors of success and/or failure of MPA effectiveness using peer-reviewed publications and first-hand expert knowledge for 27 case studies around the world. We found that stakeholder engagement was considered to be the most important factor affecting MPA success, and equally, its absence, was the most important factor influencing failure. Conversely, while some factors were identified as critical for success, their absence was not considered a driver of failure, and vice versa. This mismatch provided the impetus for considering these factors more critically. Bearing in mind that most MPAs have multiple objectives, including non-biological, this highlights the need for the development and adoption of standardized effectiveness metrics, besides biological considerations, to measure factors contributing to the success or failure of MPAs to reach their objectives. Considering our conclusions, we suggest the development of specific protocols for the assessment of stakeholder engagement, the role of leadership, the capacity of enforcement and compliance with MPAs objectives. Moreover, factors defining the success and failure of MPAs should be assessed not only by technical experts and the relevant authorities, but also by other stakeholder groups whose compliance is critical for the successful functioning of an MPA. These factors should be considered along with appropriate ecological, social, and economic data and then incorporated into adaptive management to improve MPA effectiveness. Fil: Giakoumi, Sylvaine. The University Of Queensland; Australia. University of Queensland; Australia. Université Côte D'azur; Fil: McGowan, Jennifer. University of Queensland; Australia. The University Of Queensland; Australia Fil: Mills, Morena. Imperial College London; Reino Unido. The University Of Queensland; Australia. University of Queensland; Australia Fil: Beger, Maria. University of Queensland; Australia. The University Of Queensland; Australia. University Of Leeds; Fil: Bustamante, Rodrigo H.. Csiro Oceans And Atmosphere; Australia Fil: Charles, Anthony. Saint Mary's University; Canadá Fil: Christie, Patrick. University Of Washington, Seattle; Fil: Fox, Matthew. Conservation International; Indonesia Fil: Garcia Borboroglu, Jorge Pablo. Global Penguin Society; Argentina. University Of Washington, Seattle; . Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Gelcich, Stefan. Universidad Católica de Chile; Chile. Pontificia Universidad Católica de Chile; Chile Fil: Guidetti, Paolo. Inter-university National Consortium For Marine Sciences (conisma); . Université Côte D'azur; Fil: Mackelworth, Peter. Blue World Institute Of Marine Research And Conservation; . University Of Primorska; Fil: Maina, Joseph M.. University of Queensland; Australia. The University Of Queensland; Australia Fil: McCook, Laurence. Conservation International; Indonesia. South China Seas Institute Of Oceanography Chinese Academy Of Sciences; China. James Cook University; Australia Fil: Micheli, Fiorenza. University of Stanford; Estados Unidos Fil: Morgan, Lance E.. Marine Conservation Institute; Fil: Mumby, Peter J.. University of Queensland; Australia. The University Of Queensland; Australia Fil: Reyes, Laura M.. Universidad Nacional de la Patagonia "San Juan Bosco"; Argentina. Global Penguin Society; Argentina Fil: White, Alan. Usaid, Indonesia; Indonesia. Nature Conservancy; Fil: Grorud-Colvert, Kirsten. State University of Oregon; Estados Unidos Fil: Possingham, Hugh P.. Nature Conservancy; . University of Queensland; Australia. The University Of Queensland; Australia

Globally, protected areas are being established to protect biodiversity and to promote ecosystem resilience. The typical spatial conservation planning process leading to the creation of these protected areas focuses on representation and replication of ecological features, often using decision support systems such as Marxan. Unfortunately, Marxan currently requires manual input or specialised scripts to explicitly consider ecological connectivity, a property critical to metapopulation persistence and resilience. "Marxan Connect" is a new open source, open access Graphical User Interface (GUI) designed to assist conservation planners in the systematic operationalization of ecological connectivity in protected area network planning. Marxan Connect is able to incorporate estimates of demographic connectivity (e.g. derived from tracking data, dispersal models, or genetics) or structural landscape connectivity (e.g. isolation by resistance). This is accomplished by calculating metapopulation-relevant connectivity metrics (e.g. eigenvector centrality) and treating those as conservation features, or using the connectivity data as a spatial dependency amongst sites to be included in the prioritization process. Marxan Connect allows a wide group of users to incorporate directional ecological connectivity into conservation plans. The least-cost conservation solutions provided by Marxan Connect, combined with ecologically relevant post-hoc testing, are more likely to support persistent and resilient metapopulations (e.g. fish stocks) and provide better protection for biodiversity than if connectivity is ignored.

Aim: Conservation plans often struggle to account for connectivity in spatial prioritization approaches for the protection of migratory species. Protection of such species is challenging because their movements may be uncertain and variable, span vast distances, cross international borders and traverse land and sea habitats. Often we are faced with small samples of information from various sources and the collection of additional data can be costly and time-consuming. Therefore it is important to evaluate what degree of spatial information provides sufficient results for directing management actions. Here we develop and evaluate an approach that incorporates habitat and movement information to advance the conservation of migratory species. We test our approach using information on threatened loggerhead sea turtles (Caretta caretta) in the Mediterranean. Location: The Mediterranean Sea. Methods: We use Marxan, a spatially explicit decision support tool, to select priority conservation areas. Four approaches with increasing amounts of information about the loggerhead sea turtle are compared, ranging from (1) the broad distribution, (2) multiple habitat types that represent foraging, nesting and inter-nesting habitats, (3) mark-recapture movement information to (4) telemetry-derived migration tracks. Results: We find that spatial priorities for sea turtle conservation are sensitive to the information used in the prioritization process. Setting conservation targets for migration tracks altered the location of conservation priorities, indicating that conservation plans designed without such data would miss important sea turtle habitat. We discover that even a small number of tracks make a significant contribution to a spatial conservation plan if those tracks are substantially different. Main conclusions: This study presents a novel approach to improving spatial prioritization for conserving migratory species. We propose that future telemetry studies tailor their efforts towards conservation prioritization needs, meaning that spatially dispersed samples rather than just large numbers should be obtained. This work highlights the valuable information that telemetry research contributes to the conservation of migratory species.

Important Bird and Biodiversity Areas (IBAs) are sites identified as globally important for bird species conservation. Marine IBAs are one of the few comprehensive multi-species datasets available for the marine environment, and their use in conservation planning will likely increase as countries race to protect 10% of their territorial waters by 2020. We tested 15 planning scenarios for Australia's Exclusive Economic Zone to guide best practice on integrating marine IBAs into spatial conservation prioritization. We found prioritizations based solely on habitat protection failed to protect IBAs, and prioritizations based solely on IBAs similarly failed to meet basic levels of habitat representation. Further, treating all marine IBAs as irreplaceable sites produced the most inefficient plans in terms of ecological representativeness and protection equality. Our analyses suggest that marine spatial planners who wish to use IBAs treat them like any other conservation feature by assigning them a specific protection target.

Animal-borne telemetry has revolutionized our ability to study animal movement, species physiology, demography and social structures, changing environments and the threats that animals are experiencing. While there will always be a need for basic ecological research and discovery, the current conservation crisis demands we look more pragmatically at the data required to make informed management decisions. Here, we define a framework that distinguishes how research using animal telemetry devices can influence conservation. We then discuss two critical questions which aim to directly connect telemetry-derived data to applied conservation decision-making: (i) Would my choice of action change if I had more data? (ii) Is the expected gain worth the money and time required to collect more data? Policy implications. To answer questions about integrating telemetry-derived data with applied conservation, we suggest the use of value of information analysis to quantitatively assess the return-on-investment of animal telemetry-derived data for conservation decision-making.

Protected Areas (PAs) are a central part of biodiversity conservation strategies around the world. Today, PAs cover c15% of the Earth’s land mass and c3% of the global oceans. These numbers are expected to grow rapidly to meet the Convention on Biological Diversity’s Aichi Biodiversity target 11, which aims to see 17% and 10% of terrestrial and marine biomes protected, respectively, by 2020. This target also requires countries to ensure that PAs protect an “ecologically representative” sample of their biodiversity. At present, there is no clear definition of what desirable ecological representation looks like, or guidelines of how to standardize its assessment as the PA estate grows. We propose a systematic approach to measure ecological representation in PA networks using the Protection Equality (PE) metric, which measures how equally ecological features, such as habitats, within a country’s borders are protected. Extending research in Barr et al. (2011), we present an R package and two Protection Equality (PE) measures; proportional to area PE, and fixed area PE, which measure the representativeness of a country’s PA network. We illustrate the PE metrics with two case studies: coral reef protection across countries and ecoregions in the Coral Triangle, and representation of ecoregions of six of the largest countries in the world. Our results provide repeatable transparency to the issue of representation in PA networks and provide a starting point for further discussion, evaluation and testing of representation metrics. They also highlight clear shortcomings in current PA networks, particularly where they are biased towards certain assemblage types or habitats. Our proposed metrics should be used to report on measuring progress towards the representation component of Aichi Target 11. The PE metrics can be used to measure the representation of any kind of ecological feature including: species, ecoregions, processes or habitats.