A horizon scan of global biological conservation issues for 2024.

We present the results of our 15th horizon scan of novel issues that could influence biological conservation in the future. From an initial list of 96 issues, our international panel of scientists and practitioners identified 15 that we consider important for societies worldwide to track and potentially respond to. Issues are novel within conservation or represent a substantial positive or negative step-change with global or regional extents. For example, new sources of hydrogen fuel and changes in deep-sea currents may have profound impacts on marine and terrestrial ecosystems. Technological advances that may be positive include benchtop DNA printers and the industrialisation of approaches that can create high-protein food from air, potentially reducing the pressure on land for food production.

Social vulnerability of the people exposed to wildfires in U.S. West Coast states.

Understanding of the vulnerability of populations exposed to wildfires is limited. We used an index from the U.S. Centers for Disease Control and Prevention to assess the social vulnerability of populations exposed to wildfire from 2000-2021 in California, Oregon, and Washington, which accounted for 90% of exposures in the western United States. The number of people exposed to fire from 2000-2010 to 2011-2021 increased substantially, with the largest increase, nearly 250%, for people with high social vulnerability. In Oregon and Washington, a higher percentage of exposed people were highly vulnerable (>40%) than in California (~8%). Increased social vulnerability of populations in burned areas was the primary contributor to increased exposure of the highly vulnerable in California, whereas encroachment of wildfires on vulnerable populations was the primary contributor in Oregon and Washington. Our results emphasize the importance of integrating the vulnerability of at-risk populations in wildfire mitigation and adaptation plans.

Ecological inferences about marine mammals from passive acoustic data.

Monitoring on the basis of sound recordings, or passive acoustic monitoring, can complement or serve as an alternative to real-time visual or aural monitoring of marine mammals and other animals by human observers. Passive acoustic data can support the estimation of common, individual-level ecological metrics, such as presence, detection-weighted occupancy, abundance and density, population viability and structure, and behaviour. Passive acoustic data also can support estimation of some community-level metrics, such as species richness and composition. The feasibility of estimation and certainty of estimates is highly context dependent, and understanding the factors that affect the reliability of measurements is useful for those considering whether to use passive acoustic data. Here, we review basic concepts and methods of passive acoustic sampling in marine systems that often are applicable to marine mammal research and conservation. Our ultimate aim is to facilitate collaboration among ecologists, bioacousticians, and data analysts. Ecological applications of passive acoustics require one to make decisions about sampling design, which in turn requires consideration of sound propagation, sampling of signals, and data storage. One also must make decisions about signal detection and classification and evaluation of the performance of algorithms for these tasks. Investment in the research and development of systems that automate detection and classification, including machine learning, are increasing. Passive acoustic monitoring is more reliable for detection of species presence than for estimation of other species-level metrics. Use of passive acoustic monitoring to distinguish among individual animals remains difficult. However, information about detection probability, vocalisation or cue rate, and relations between vocalisations and the number and behaviour of animals increases the feasibility of estimating abundance or density. Most sensor deployments are fixed in space or are sporadic, making temporal turnover in species composition more tractable to estimate than spatial turnover. Collaborations between acousticians and ecologists are most likely to be successful and rewarding when all partners critically examine and share a fundamental understanding of the target variables, sampling process, and analytical methods.

A global biological conservation horizon scan of issues for 2023.

We present the results of our 14th horizon scan of issues we expect to influence biological conservation in the future. From an initial set of 102 topics, our global panel of 30 scientists and practitioners identified 15 issues we consider most urgent for societies worldwide to address. Issues are novel within biological conservation or represent a substantial positive or negative step change at global or regional scales. Issues such as submerged artificial light fisheries and accelerating upper ocean currents could have profound negative impacts on marine or coastal ecosystems. We also identified potentially positive technological advances, including energy production and storage, improved fertilisation methods, and expansion of biodegradable materials. If effectively managed, these technologies could realise future benefits for biological diversity.

Silbido profundo: An open source package for the use of deep learning to detect odontocete whistles.

This work presents an open-source matlab software package for exploiting recent advances in extracting tonal signals from large acoustic data sets. A whistle extraction algorithm published by Li, Liu, Palmer, Fleishman, Gillespie, Nosal, Shiu, Klinck, Cholewiak, Helble, and Roch [(2020). Proceedings of the International Joint Conference on Neural Networks, July 19-24, Glasgow, Scotland, p. 10] is incorporated into silbido, an established software package for extraction of cetacean tonal calls. The precision and recall of the new system were over 96% and nearly 80%, respectively, when applied to a whistle extraction task on a challenging two-species subset of a conference-benchmark data set. A second data set was examined to assess whether the algorithm generalized to data that were collected across different recording devices and locations. These data included 487 h of weakly labeled, towed array data collected in the Pacific Ocean on two National Oceanographic and Atmospheric Administration (NOAA) cruises. Labels for these data consisted of regions of toothed whale presence for at least 15 species that were based on visual and acoustic observations and not limited to whistles. Although the lack of per whistle-level annotations prevented measurement of precision and recall, there was strong concurrence of automatic detections and the NOAA annotations, suggesting that the algorithm generalizes well to new data.

Multiple-region, N-mixture community model to assess associations of riparian area, fragmentation, and species richness.

The associations of habitat area and fragmentation with species richness long have been major topics within community ecology. Recent discussion has focused on properly assessing fragmentation independent of habitat area (fragmentation per se), and on whether fragmentation has significant negative or positive associations with species richness. We created a novel, multiple-region, N-mixture community model (MNCM) to examine the relations of riparian area and fragmentation with species richness of breeding birds in mountain ranges within the Great Basin, Nevada, USA. Our MNCM accounts for imperfect detection in count data at the survey-point level while allowing comparisons of species richness among regions in which those points are embedded. We used individual canyons within mountain ranges as regions in our model and measured riparian area and the Normalized Landscape Shape Index, a metric of fragmentation that is independent of total riparian area. We found that riparian area, but not its fragmentation, was a primary predictor of canyon-level species richness of both riparian obligates and all species. The relationship between riparian area and riparian obligate species richness was nonlinear: canyons with ≥25 ha woody riparian vegetation had relatively high species richness, whereas species richness was considerably lower in canyons with <25 ha. Our MNCM can be used to calculate other metrics of diversity that require abundance estimates. For example, Simpson's evenness of riparian obligate species had a weak negative association with riparian area and was not associated with fragmentation. Projections of future riparian contraction suggested that decreases in species richness are likely to be greatest in canyons that currently have moderate (~10-25 ha) amounts of riparian vegetation. Our results suggest that if a goal of management is to maximize the species richness of breeding birds in montane riparian areas in the Great Basin, it may be more effective to focus on total habitat area than on fragmentation of patches within canyons, and that canyons with at least moderate amounts of riparian vegetation should be prioritized.

A horizon scan of global biological conservation issues for 2022.

We present the results of our 13th annual horizon scan of issues likely to impact on biodiversity conservation. Issues are either novel within the biological conservation sector or could cause a substantial step-change in impact, either globally or regionally. Our global panel of 26 scientists and practitioners identified 15 issues that we believe to represent the highest priorities for tracking and action. Many of the issues we identified, including the impact of satellite megaconstellations and the use of long-distance wireless energy transfer, have both elements of threats and emerging opportunities. A recent state-sponsored application to commence deep-sea mining represents a significant step-change in impact. We hope that this horizon scan will increase research and policy attention on the highlighted issues.

Improve automatic detection of animal call sequences with temporal context.

Many animals rely on long-form communication, in the form of songs, for vital functions such as mate attraction and territorial defence. We explored the prospect of improving automatic recognition performance by using the temporal context inherent in song. The ability to accurately detect sequences of calls has implications for conservation and biological studies. We show that the performance of a convolutional neural network (CNN), designed to detect song notes (calls) in short-duration audio segments, can be improved by combining it with a recurrent network designed to process sequences of learned representations from the CNN on a longer time scale. The combined system of independently trained CNN and long short-term memory (LSTM) network models exploits the temporal patterns between song notes. We demonstrate the technique using recordings of fin whale (Balaenoptera physalus) songs, which comprise patterned sequences of characteristic notes. We evaluated several variants of the CNN + LSTM network. Relative to the baseline CNN model, the CNN + LSTM models reduced performance variance, offering a 9-17% increase in area under the precision-recall curve and a 9-18% increase in peak F1-scores. These results show that the inclusion of temporal information may offer a valuable pathway for improving the automatic recognition and transcription of wildlife recordings.

A 2021 Horizon Scan of Emerging Global Biological Conservation Issues.

We present the results from our 12th annual horizon scan of issues likely to impact biological conservation in the future. From a list of 97 topics, our global panel of 25 scientists and practitioners identified the top 15 issues that we believe society may urgently need to address. These issues are either novel in the biological conservation sector or represent a substantial positive or negative step-change in impact at global or regional level. Six issues, such as coral reef deoxygenation and changes in polar coastal productivity, affect marine or coastal ecosystems and seven relate to human and ecosystem-level responses to climate change. Identification of potential forthcoming issues for biological conservation may enable increased preparedness by researchers, practitioners, and decision-makers.

Publisher Correction: Deep neural networks for automated detection of marine mammal species.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Associations of breeding-bird abundance with climate vary among species and trait-based groups in southern California.

The responses of individuals and populations to climate change vary as functions of physiology, ecology, and plasticity. We investigated whether annual variation in seasonal temperature and precipitation was associated with relative abundances of breeding bird species at local and regional levels in southern California, USA, from 1968-2013. We tested our hypotheses that abundances were correlated positively with precipitation and negatively with temperature in this semiarid to arid region. We also examined whether responses to climate varied among groups of species with similar land-cover associations, nesting locations, and migratory patterns. We investigated relations between seasonal climate variables and the relative abundances of 41 species as estimated by the North American Breeding Bird Survey. Associations with climate variables varied among species. Results of models of species associated with arid scrublands or that nest on the ground strongly supported our hypotheses, whereas those of species associated with coniferous forests or that nest in cavities did not. Associations between climate variables and the abundances of other trait-based groups were diverse. Our results suggest that species in arid areas may be negatively affected by increased temperature and aridity, but species in nearby areas that are cooler and less arid may respond positively to those fluctuations in climate. Relations with climate variables can differ among similar species, and such knowledge may inform projections of future abundance trajectories and geographic ranges.

Deep neural networks for automated detection of marine mammal species.

Deep neural networks have advanced the field of detection and classification and allowed for effective identification of signals in challenging data sets. Numerous time-critical conservation needs may benefit from these methods. We developed and empirically studied a variety of deep neural networks to detect the vocalizations of endangered North Atlantic right whales (Eubalaena glacialis). We compared the performance of these deep architectures to that of traditional detection algorithms for the primary vocalization produced by this species, the upcall. We show that deep-learning architectures are capable of producing false-positive rates that are orders of magnitude lower than alternative algorithms while substantially increasing the ability to detect calls. We demonstrate that a deep neural network trained with recordings from a single geographic region recorded over a span of days is capable of generalizing well to data from multiple years and across the species' range, and that the low false positives make the output of the algorithm amenable to quality control for verification. The deep neural networks we developed are relatively easy to implement with existing software, and may provide new insights applicable to the conservation of endangered species.

A Horizon Scan of Emerging Global Biological Conservation Issues for 2020.

In this horizon scan, we highlight 15 emerging issues of potential relevance to global conservation in 2020. Seven relate to potentially extensive changes in vegetation or ecological systems. These changes are either relatively new, for example, conversion of kelp forests to simpler macroalgal systems, or may occur in the future, for example, as a result of the derivation of nanocelluose from wood or the rapid expansion of small hydropower schemes. Other topics highlight potential changes in national legislation that may have global effect on international agreements. Our panel of 23 scientists and practitioners selected these issues using a modified version of the Delphi technique from a long-list of 89 potential topics.

Quantifying Ecological Integrity of Terrestrial Systems to Inform Management of Multiple-Use Public Lands in the United States.

The concept of ecological integrity has been applied widely to management of aquatic systems, but still is considered by many to be too vague and difficult to quantify to be useful for managing terrestrial systems, particularly across broad areas. Extensive public lands in the western United States are managed for diverse uses such as timber harvest, livestock grazing, energy development, and wildlife conservation, some of which may degrade ecological integrity. We propose a method for assessing ecological integrity on multiple-use lands that identifies the components of integrity and levels in the ecological hierarchy where the assessment will focus, and considers existing policies and management objectives. Both natural reference and societally desired environmental conditions are relevant comparison points. We applied the method to evaluate the ecological integrity of shrublands in Nevada, yielding an assessment based on six indicators of ecosystem structure, function, and composition, including resource- and stressor-based indicators measured at multiple scales. Results varied spatially and among indicators. Invasive plant cover and surface development were highest in shrublands in northwest and southeast Nevada. Departure from reference conditions of shrubland area, composition, patch size, and connectivity was highest in central and northern Nevada. Results may inform efforts to control invasive species and restore shrublands on federal lands in Nevada. We suggest that ecological integrity assessments for multiple-use lands be grounded in existing policies and monitoring programs, incorporate resource- and stressor-based metrics, rely on publicly available data collected at multiple spatial scales, and quantify both natural reference and societally desired resource conditions.

Ten Years On: A Review of the First Global Conservation Horizon Scan.

Our first horizon scan, conducted in 2009, aimed to identify novel but poorly known issues with potentially significant effects on global conservation of biological diversity. Following completion of the tenth annual scan, we reviewed the 15 topics identified a decade ago and assessed their development in the scientific literature and news media. Five topics, including microplastic pollution, synthetic meat, and environmental applications of mobile-sensing technology, appeared to have had widespread salience and effects. The effects of six topics were moderate, three have not emerged, and the effects of one topic were low. The awareness of, and involvement in, these issues by 12 conservation organisations has increased for most issues since 2009.

A Horizon Scan of Emerging Issues for Global Conservation in 2019.

We present the results of our tenth annual horizon scan. We identified 15 emerging priority topics that may have major positive or negative effects on the future conservation of global biodiversity, but currently have low awareness within the conservation community. We hope to increase research and policy attention on these areas, improving the capacity of the community to mitigate impacts of potentially negative issues, and maximise the benefits of issues that provide opportunities. Topics include advances in crop breeding, which may affect insects and land use; manipulations of natural water flows and weather systems on the Tibetan Plateau; release of carbon and mercury from melting polar ice and thawing permafrost; new funding schemes and regulations; and land-use changes across Indo-Malaysia.

Understanding the population consequences of disturbance.

Managing the nonlethal effects of disturbance on wildlife populations has been a long-term goal for decision makers, managers, and ecologists, and assessment of these effects is currently required by European Union and United States legislation. However, robust assessment of these effects is challenging. The management of human activities that have nonlethal effects on wildlife is a specific example of a fundamental ecological problem: how to understand the population-level consequences of changes in the behavior or physiology of individual animals that are caused by external stressors. In this study, we review recent applications of a conceptual framework for assessing and predicting these consequences for marine mammal populations. We explore the range of models that can be used to formalize the approach and we identify critical research gaps. We also provide a decision tree that can be used to select the most appropriate model structure given the available data. Synthesis and applications: The implementation of this framework has moved the focus of discussion of the management of nonlethal disturbances on marine mammal populations away from a rhetorical debate about defining negligible impact and toward a quantitative understanding of long-term population-level effects. Here we demonstrate the framework's general applicability to other marine and terrestrial systems and show how it can support integrated modeling of the proximate and ultimate mechanisms that regulate trait-mediated, indirect interactions in ecological communities, that is, the nonconsumptive effects of a predator or stressor on a species' behavior, physiology, or life history.

A 2018 Horizon Scan of Emerging Issues for Global Conservation and Biological Diversity.

This is our ninth annual horizon scan to identify emerging issues that we believe could affect global biological diversity, natural capital and ecosystem services, and conservation efforts. Our diverse and international team, with expertise in horizon scanning, science communication, as well as conservation science, practice, and policy, reviewed 117 potential issues. We identified the 15 that may have the greatest positive or negative effects but are not yet well recognised by the global conservation community. Themes among these topics include new mechanisms driving the emergence and geographic expansion of diseases, innovative biotechnologies, reassessments of global change, and the development of strategic infrastructure to facilitate global economic priorities.

A 2017 Horizon Scan of Emerging Issues for Global Conservation and Biological Diversity.

We present the results of our eighth annual horizon scan of emerging issues likely to affect global biological diversity, the environment, and conservation efforts in the future. The potential effects of these novel issues might not yet be fully recognized or understood by the global conservation community, and the issues can be regarded as both opportunities and risks. A diverse international team with collective expertise in horizon scanning, science communication, and conservation research, practice, and policy reviewed 100 potential issues and identified 15 that qualified as emerging, with potential substantial global effects. These issues include new developments in energy storage and fuel production, sand extraction, potential solutions to combat coral bleaching and invasive marine species, and blockchain technology.