Andrew Chin  Fergus John Molloy  Darren Cameron  Jon C. Day  Jessica Cramp  Karin Leeann Gerhardt  Michelle R. Heupel  Mark Read  Colin A. Simpfendorfer 《Conservation biology》2023,37(1):e13917

Marine protected areas (MPAs) are key tools in addressing the global decline of sharks and rays, and marine parks and shark sanctuaries of various configurations have been established to conserve shark populations. However, assessments of their efficacy are compromised by inconsistent terminology, lack of standardized approaches to assess how MPAs contribute to shark and ray conservation, and ambiguity about how to integrate movement data in assessment processes. We devised a conceptual framework to standardize key terms (e.g., protection, contribution, potential impact, risk, threat) and used the concept of portfolio risk to identify key attributes of sharks and rays (assets), the threats they face (portfolio risk), and the specific role of MPAs in risk mitigation (insurance). Movement data can be integrated into the process by informing risk exposure and mitigation through MPAs. The framework is operationalized by posing 8 key questions that prompt practitioners to consider the assessment scope, MPA type and purpose, range of existing and potential threats, species biology and ecology, and management and operational contexts. Ultimately, MPA contributions to shark and ray conservation differ according to a complex set of human and natural factors and interactions that should be carefully considered in MPA design, implementation, and evaluation.  相似文献   

    

Enrico Di Minin  Christoph Fink  Anna Hausmann  Jens Kremer  Ritwik Kulkarni 《Conservation biology》2021,35(2):437-446

Social media data are being increasingly used in conservation science to study human–nature interactions. User-generated content, such as images, video, text, and audio, and the associated metadata can be used to assess such interactions. A number of social media platforms provide free access to user-generated social media content. However, similar to any research involving people, scientific investigations based on social media data require compliance with highest standards of data privacy and data protection, even when data are publicly available. Should social media data be misused, the risks to individual users' privacy and well-being can be substantial. We investigated the legal basis for using social media data while ensuring data subjects’ rights through a case study based on the European Union's General Data Protection Regulation. The risks associated with using social media data in research include accidental and purposeful misidentification that has the potential to cause psychological or physical harm to an identified person. To collect, store, protect, share, and manage social media data in a way that prevents potential risks to users involved, one should minimize data, anonymize data, and follow strict data management procedure. Risk-based approaches, such as a data privacy impact assessment, can be used to identify and minimize privacy risks to social media users, to demonstrate accountability and to comply with data protection legislation. We recommend that conservation scientists carefully consider our recommendations in devising their research objectives so as to facilitate responsible use of social media data in conservation science research, for example, in conservation culturomics and investigations of illegal wildlife trade online.  相似文献   

    

Luca Santini  Stuart H. M. Butchart  Carlo Rondinini  Ana Benítez-López  Jelle P. Hilbers  Aafke M. Schipper  Mirza Cengic  Joseph A. Tobias  Mark A. J. Huijbregts 《Conservation biology》2019,33(5):1084-1093

The IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species’ distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land-cover change, species-specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5–2.3% and 6.4–14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early-warning system to identify species potentially warranting changes in their extinction-risk category based on periodic updates of land-cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment.  相似文献   

    

Judi E. Hewitt  Carolyn J. Lundquist  Joanne Ellis 《Conservation biology》2019,33(1):142-151

Analysis of the biological traits (e.g., feeding mode and size) that control how organisms interact with their environment has been used to identify environmental drivers of, or impacts on, species and to explain the importance of biodiversity loss. Biological trait analysis (BTA) could also be used within risk-assessment frameworks or in conservation planning if one understands the groups of traits that predict the sensitivity of habitats or communities to specific human activities. Deriving sensitivities from BTA should extend sensitivity predictions to a variety of habitats, especially those in which it would be difficult to conduct experiments (e.g., due to depth or risk to human life) and to scales beyond the norm of most experiments. We used data on epibenthos, collected via video along transects at 27 sites in a relatively pristine region of the seafloor, to determine scales of natural spatial variability of derived sensitivities and the degree to which predictions of sensitivity differed among 3 stressors (extraction of species, sedimentation, and suspended sediments) or were affected by underlying community compositions. We used 3 metrics (weighted abundance, abundance of highly sensitive species, and number of highly sensitive species) to derive sensitivity to these stressors and simulated the ability of these metrics to detect a range of stressor intensities. Regardless of spatial patterns of sensitivities across the sampled area, BTA distinguished differences in sensitivity to different stressors. The BTA also successfully separated differences in community composition from differences in sensitivity to stressors. Conversely, the 3 metrics differed widely in their ability to detect simulated impacts and likely reflect underlying ecological processes, suggesting that use of multiple metrics would be informative for spatial planning and allocating conservation priorities. Our results suggest BTA could be used as a first step in strategic prioritization of protected areas and as an underlying layer for spatial planning.  相似文献   

    

Caitlin C. Mothes  Stephanie L. Clements  Dishane K. Hewavithana  Hunter J. Howell  Aaron S. David  Nicole D. Leventhal  Christopher A. Searcy 《Conservation biology》2020,34(3):754-761

Standardized classification methods based on quantifiable risk metrics are critical for evaluating extinction threats because they increase objectivity, consistency, and transparency of listing decisions. Yet, in the United States, neither federal nor state agencies use standardized methods for listing species for legal protection, which could put listing decisions at odds with the magnitude of the risk. We used a recently developed set of quantitative risk metrics for California herpetofauna as a case study to highlight discrepancies in listing decisions made without standardized methods. We also combined such quantitative metrics with classification tree analysis to attempt to increase the transparency of previous listing decisions by identifying the criteria that had inherently been given the most weight. Federally listed herpetofauna in California scored significantly higher on the risk-metric spectrum than those not federally listed, whereas state-listed species did not score any higher than species that were not state listed. Based on classification trees, state endemism was the most important predictor of listing status at the state level and distribution trend (decline in a species’ range size) and population trend (decline in a species’ abundance at localized sites) were the most important predictors at the federal level. Our results emphasize the need for governing bodies to adopt standardized methods for assessing conservation risk that are based on quantitative criteria. Such methods allow decision makers to identify criteria inherently given the most weight in determining listing status, thus increasing the transparency of previous listing decisions, and produce an unbiased comparison of conservation threat across all species to promote consistency, efficiency, and effectiveness of the listing process.  相似文献