Near-term ecological forecasting for dynamic aeroconservation of migratory birds

Near-term ecological forecasting has the potential to mitigate negative impacts of human modifications on wildlife by directing efficient action through relevant and timely predictions. We used the U.S. avian migration system to highlight ecological forecasting applications for aeroconservation. We used millions of observations from 143 weather surveillance radars to construct and evaluate a migration forecasting system for nocturnal bird migration over the contiguous United States. We identified the number of nights of mitigation required to reduce the risk of aerial hazards to 50% of avian migrants passing a given area in spring and autumn based on dynamic forecasts of migration activity. We also investigated an alternative approach, that is, employing a fixed conservation strategy based on time windows that historically capture 50% of migratory passage. In practice, during both spring and autumn, dynamic forecasts required fewer action nights compared with fixed window selection at all locations (spring: mean of 7.3 more alert days; fall: mean of 12.8 more alert days). This pattern resulted in part from the pulsed nature of bird migration captured in the radar data, where the majority (54.3%) of birds move on 10% of a migration season's nights. Our results highlight the benefits of near-term ecological forecasting and the potential advantages of dynamic mitigation strategies over static ones, especially in the face of increasing risks to migrating birds from light pollution, wind energy infrastructure, and collisions with structures.     

Modeling scale up of anthropogenic impacts from individual pollinator behavior to pollination systems

Understanding how anthropogenic disturbances affect plant–pollinator systems has important implications for the conservation of biodiversity and ecosystem functioning. Previous laboratory studies show that pesticides and pathogens, which have been implicated in the rapid global decline of pollinators over recent years, can impair behavioral processes needed for pollinators to adaptively exploit floral resources and effectively transfer pollen among plants. However, the potential for these sublethal stressor effects on pollinator–plant interactions at the individual level to scale up into changes to the dynamics of wild plant and pollinator populations at the system level remains unclear. We developed an empirically parameterized agent-based model of a bumblebee pollination system called SimBee to test for effects of stressor-induced decreases in the memory capacity and information processing speed of individual foragers on bee abundance (scenario 1), plant diversity (scenario 2), and bee–plant system stability (scenario 3) over 20 virtual seasons. Modeling of a simple pollination network of a bumblebee and four co-flowering bee-pollinated plant species indicated that bee decline and plant species extinction events could occur when only 25% of the forager population showed cognitive impairment. Higher percentages of impairment caused 50% bee loss in just five virtual seasons and system-wide extinction events in less than 20 virtual seasons under some conditions. Plant species extinctions occurred regardless of bee population size, indicating that stressor-induced changes to pollinator behavior alone could drive species loss from plant communities. These findings indicate that sublethal stressor effects on pollinator behavioral mechanisms, although seemingly insignificant at the level of individuals, have the cumulative potential in principle to degrade plant–pollinator species interactions at the system level. Our work highlights the importance of an agent-based modeling approach for the identification and mitigation of anthropogenic impacts on plant–pollinator systems.     

Conservation and social outcomes of private protected areas

Government administered protected areas (PAs) have dominated conservation strategies, discourse, and research, yet private actors are increasingly managing land for conservation. Little is known about the social and environmental outcomes of these privately protected areas (PPAs). We searched the global literature in English on PPAs and their environmental and social outcomes and identified 412 articles suitable for inclusion. Research on PPAs was geographically skewed; more studies occurred in the United States. Environmental outcomes of PPAs were mostly positive (89%), but social outcomes of PPAs were reported less (12% of all studies), and these outcomes were more mixed (65% positive). Private protected areas increased the number or extent of ecosystems, ecoregions, or species covered by PAs (representativeness) and PA network connectivity and effectively reduced deforestation and restored degraded lands. Few PPA owners reported negative social outcomes, experienced improved social capital, increased property value, or a reduction in taxes. Local communities benefited from increased employment, training, and community-wide development (e.g., building of schools), but they reported reduced social capital and no significant difference to household income. The causal mechanisms through which PPAs influence social and environmental outcomes remain unclear, as does how political, economic, and social contexts shape these mechanisms. Future research should widen the geographical scope and diversify the types of PPAs studied and focus on determining the casual mechanisms through which PPA outcomes occur in different contexts. We propose an assessment framework that could be adopted to facilitate this process.     

How to address data privacy concerns when using social media data in conservation science

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.     

Exploring human–nature interactions in national parks with social media photographs and computer vision

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human–nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human–nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.     

Digital data sources and methods for conservation culturomics

Ongoing loss of biological diversity is primarily the result of unsustainable human behavior. Thus, the long-term success of biodiversity conservation depends on a thorough understanding of human–nature interactions. Such interactions are ubiquitous but vary greatly in time and space and are difficult to monitor efficiently at large spatial scales. However, the Information Age also provides new opportunities to better understand human–nature interactions because many aspects of daily life are recorded in a variety of digital formats. The emerging field of conservation culturomics aims to take advantage of digital data sources and methods to study human–nature interactions and thus to provide new tools for studying conservation at relevant temporal and spatial scales. Nevertheless, technical challenges associated with the identification, access, and analysis of relevant data hamper the wider adoption of culturomics methods. To help overcome these barriers, we propose a conservation culturomics research framework that addresses data acquisition, analysis, and inherent biases. The main sources of culturomic data include web pages, social media, and other digital platforms from which metrics of content and engagement can be obtained. Obtaining raw data from these platforms is usually desirable but requires careful consideration of how to access, store, and prepare the data for analysis. Methods for data analysis include network approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.     

Wildlife collection for scientific purposes

Illegal transfer of wildlife has 2 main purposes: trade and scientific research. Trade is the most common, whereas scientific research is much less common and unprofitable, yet still important. Biopiracy in science is often neglected despite that many researchers encounter it during their careers. The use of illegally acquired specimens is detected in different research fields, from scientists bioprospecting for new pharmacological substances, to taxonomists working on natural history collections, to researchers working in zoos, aquariums, and botanical gardens. The practice can be due to a lack of knowledge about the permit requirements in different countries or, probably most often, to the generally high level of bureaucracy associated with rule compliance. Significant regulatory filters to avoid biopiracy can be provided by different stakeholders. Natural history collection hosts should adopt strict codes of conduct; editors of scientific publications should require authors to declare that all studied specimens were acquired legally and to cite museum catalog numbers as guarantee of best practices. Scientific societies should actively encourage publication in peer-reviewed journals of work in which specimens collected from the wild were used. The International Commission on Zoological Nomenclature could require newly designated types based on recently collected specimens to be accompanied by statements of deposition in recognized scientific or educational institutions. We also propose the creation of an online platform that gathers information about environmental regulations and permits required for scientific activities in different countries and respective responsible governmental agencies and the simplification of the bureaucracy related to regulating scientific activities. This would make regulations more agile and easier to comply with. The global biodiversity crisis means data need to be collected ever faster, but biopiracy is not the answer and undermines the credibility of science and researchers. It is critical to find a modus vivendi that promotes compliance with regulations and scientific progress.     

The challenge of biased evidence in conservation

Efforts to tackle the current biodiversity crisis need to be as efficient and effective as possible given chronic underfunding. To inform decision-makers of the most effective conservation actions, it is important to identify biases and gaps in the conservation literature to prioritize future evidence generation. We used the Conservation Evidence database to assess the state of the global literature that tests conservation actions for amphibians and birds. For the studies in the database, we investigated their spatial and taxonomic extent and distribution across biomes, effectiveness metrics, and study designs. Studies were heavily concentrated in Western Europe and North America for birds and particularly for amphibians, and temperate forest and grassland biomes were highly represented relative to their percentage of land coverage. Studies that used the most reliable study designs—before-after control-impact and randomized controlled trials—were the most geographically restricted and scarce in the evidence base. There were negative spatial relationships between the numbers of studies and the numbers of threatened and data-deficient species worldwide. Taxonomic biases and gaps were apparent for amphibians and birds—some entire orders were absent from the evidence base—whereas others were poorly represented relative to the proportion of threatened species they contained. Metrics used to evaluate effectiveness of conservation actions were often inconsistent between studies, potentially making them less directly comparable and evidence synthesis more difficult. Testing conservation actions on threatened species outside Western Europe, North America, and Australasia should be prioritized. Standardizing metrics and improving the rigor of study designs used to test conservation actions would also improve the quality of the evidence base for synthesis and decision-making.     

Motivations for the use and consumption of wildlife products

The dominant approach to combating the illegal wildlife trade has traditionally been to restrict the supply of wildlife products. Yet conservationists increasingly recognize the importance of implementing demand-side interventions that target the end consumers in the trade chain. Their aim is to curb the consumption of wildlife or shift consumption to more sustainable alternatives. However, there are still considerable knowledge gaps in understanding of the diversity of consumer motivations in the context of illegal wildlife trade, which includes hundreds of thousands of species, different uses, and diverse contexts. Based on consultation with multiple experts from a diversity of backgrounds, nationalities, and focal taxa, we developed a typology of common motivations held by wildlife consumers that can be used to inform conservation interventions. We identified 5 main motivational categories for wildlife use: experiential, social, functional, financial, and spiritual, each containing subcategories. This framework is intended to facilitate the segmentation of consumers based on psychographics and allow the tailoring of interventions—whether behavior change campaigns, enforcement efforts, or incentive programs—to the specific context in which they will be used. Underlining the importance of consumer research and collaborating with local actors is an important step toward promoting a more systematic approach to the design of demand reduction interventions.     

Rewilding in the face of climate change

Expansion of the global protected-area network has been proposed as a strategy to address threats from accelerating climate change and species extinction. A key step in increasing the effectiveness of such expansion is understanding how novel threats to biodiversity from climate change alter concepts such as rewilding, which have underpinned many proposals for large interconnected reserves. We reviewed potential challenges that climate change poses to rewilding and found that the conservation value of large protected areas persists under climate change. Nevertheless, more attention should be given to protection of microrefugia, macrorefugia, complete environmental gradients, and areas that connect current and future suitable climates and to maintaining ecosystem processes and stabilizing feedbacks via conservation strategies that are resilient to uncertainty regarding climate trends. Because a major element of the threat from climate change stems from its novel geographic patterns, we examined, as an example, the implications for climate-adaptation planning of latitudinal, longitudinal (continental to maritime), and elevational gradients in climate-change exposure across the Yellowstone-to-Yukon region, the locus of an iconic conservation proposal initially designed to conserve wide-ranging carnivore species. In addition to a continued emphasis on conserving intact landscapes, restoration of degraded low-elevation areas within the region is needed to capture sites important for landscape-level climate resilience. Extreme climate exposure projected for boreal North America suggests the need for ambitious goals for expansion of the protected-area network there to include refugia created by topography and ecological features, such as peatlands, whose conservation can also reduce emissions from carbon stored in soil. Qualitative understanding of underlying reserve design rules and the geography of climate-change exposure can strengthen the outcomes of inclusive regional planning processes that identify specific sites for protection.