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.     

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.     

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.     

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.     

Reliability of social media data in monitoring the global pet trade in ants

The global pet trade is a major risk to biodiversity and humans and has become increasingly globalized, diversified, digitalized, and extremely difficult to control. With billions of internet users posting online daily, social media could be a powerful surveillance tool. But it is unknown how reliably social media can track the global pet trade. We tested whether Instagram data predicted the geographic distribution of pet stores and the taxonomic composition of traded species in the emerging pet trade in ants (Hymenoptera, Formicidae). We visited 138 online stores selling ants as pets worldwide and recorded the species traded. We scraped ∼38,000 Instagram posts from ∼6300 users referencing ants as pets and analyzed comments on post and geolocation (available for ∼1800 users). We tested whether the number of Instagram users predicted the number of ant sellers per country and whether the species referenced as pets on Instagram matched the species offered in online stores, with a particular focus on invasive species. The location of Instagram users referencing ants as pets predicted the location of ant sellers across the globe (R² = 0.87). Instagram data detected 439 of the 631 ant species traded in online stores (70%), including 59 of the 68 invasive species traded (87%). The number of Instagram users referencing a species was a good predictor of the number of sellers offering the species (R² = 0.77). Overall, Instagram data provided affordable and reliable data for monitoring the emerging pet trade in ants. Easier access to these data would facilitate monitoring of the global pet trade and help implement relevant regulations in a timely manner.     

Global assessment of the biodiversity safeguards of development banks that finance infrastructure

Infrastructure development is a major driver of biodiversity loss globally. With upward of US$2.5 trillion in annual investments in infrastructure, the financial sector indirectly drives this biodiversity loss. At the same time, biodiversity safeguards (project-level biodiversity impact mitigation requirements) of infrastructure financiers can help limit this damage. The coverage and harmonization of biodiversity safeguards are important factors in their effectiveness and therefore warrant scrutiny. It is equally important to examine the extent to which these safeguards align with best-practice principles for biodiversity impact mitigation outlined in international policies, such as that of the International Union for Conservation of Nature. We assessed the biodiversity safeguards of public development banks and development finance institutions for coverage, harmonization, and alignment with best practice. We used Institute of New Structural Economics and Agence Française de Développement's global database to identify development banks that invest in high-biodiversity-footprint infrastructure and have over US$500 million in assets. Of the 155 banks, 42% (n = 65) had biodiversity safeguards. Of the existing safeguards, 86% (56 of 65) were harmonized with International Finance Corporation (IFC) Performance Standard 6 (PS6). The IFC PS6 (and by extension the 56 safeguard policies harmonized with it) had high alignment with international best practice in biodiversity impact mitigation, whereas the remaining 8 exhibited partial alignment, incorporating few principles that clarify the conditions for effective biodiversity offsetting. Given their dual role in setting benchmarks and leveraging private finance, infrastructure financiers in development finance need to adopt best-practice biodiversity safeguards if the tide of global biodiversity loss is to be stemmed. The IFC PS6, if strengthened, can act as a useful template for other financier safeguards. The high degree of harmonization among safeguards is promising, pointing to a potential for diffusion of practices.     

A landscape of conservation philanthropy for U.S. land trusts

Finding ways to increase financial support is critical to conservation efforts. We used conservation fundraising data, unprecedented in their resolution, to reveal spatial patterns in philanthropic giving to a major land protection organization in the United States. We also quantified the relationship between the amount of effort devoted to fundraising and donations received. Around 40% of the variation in the propensity to give and overall value of gifts was explained by sociodemographic and other predictors. For example, education level had greater predictive capacity than income, political views, and other factors often considered important. Fundraising effort was strongly predictive of the amount donated in an area. Our model estimated a doubling of funds raised with a 5-fold increase of effort. Conservation organizations could use our statistical framework to inform efforts aimed at increasing philanthropic giving by identifying locations with large model residuals. An example application of our framework showed an almost 40% increase (US$200 million) in fundraising revenue for the case-study conservation organization.     

Meta-analysis of the effects of upstream land cover on stream recovery

Unpredictable or variable ecosystem recovery from disturbance presents a challenge to conservation, particularly as the scale of human disturbance continues to increase. Theory suggests land-cover and disturbance characteristics affect recovery, but individual studies of disturbance and recovery frequently struggle to uncover generalizable patterns because of high levels of site-specific variation. To understand how land-cover, disturbance type, and disturbance duration influence ecosystem recovery, we used studies documenting recovery of 50 streams to perform a global meta-analysis of stream recovery from disturbances that affect water quality (e.g., oil spill, fire, wastewater). We extracted upstream natural and urban land-cover percentages for each site and performed model selection and averaging to identify influences on recovery completeness. Most streams improved following the end of a disturbance (median 240% of disturbed condition) but did not recover fully to baseline predisturbance condition within the studied period (median study period 2 years; median recovery 60% of baseline). Scale of disturbance in time and space did not predict recovery, but sites with higher percentages of upstream natural land cover had less complete recovery relative to sites with more urban or agricultural cover, possibly due to higher baseline conditions in these streams. Our findings suggest impacts to systems with low anthropogenic stress may be more irreversible than impacts to already modified systems. We call for more long-term evaluations of ecosystem response to disturbance and the inclusion of regional references and predisturbance reference conditions for comparison. A more thorough understanding of the role of the surrounding landscape in shaping stream response to disturbance can help managers calibrate expectations for recovery and prioritize protection.