Discovering and developing primary biodiversity data from social networking sites: A novel approach

Increasing biodiversity knowledge through social media: A case study from tropical Bangladesh

Citizen science programs are becoming increasingly popular among naturalists but remain heavily biased taxonomically and geographically. However, with the explosive popularity of social media and the near-ubiquitous availability of smartphones, many post wildlife photographs on social media. Here, we illustrate the potential of harvesting these data to enhance our biodiversity understanding using Bangladesh, a tropical biodiverse country, as a case study. We compared biodiversity records extracted from Facebook with those from the Global Biodiversity Information Facility (GBIF), collating geospatial records for 1013 unique species, including 970 species from Facebook and 712 species from GBIF. Although most observation records were biased toward major cities, the Facebook records were more evenly spatially distributed. About 86% of the Threatened species records were from Facebook, whereas the GBIF records were almost entirely Of Least Concern species. To reduce the global biodiversity data shortfall, a key research priority now is the development of mechanisms for extracting and interpreting social media biodiversity data.

Investigating the potential of social media and citizen science data to track changes in species' distributions

How to best track species as they rapidly alter their distributions in response to climate change has become a key scientific priority. Information on species distributions is derived from biological records, which tend to be primarily sourced from traditional recording schemes, but increasingly also by citizen science initiatives and social media platforms, with biological recording having become more accessible to the general public. To date, however, our understanding of the respective potential of social media and citizen science to complement the information gathered by traditional recording schemes remains limited, particularly when it comes to tracking species on the move with climate change. To address this gap, we investigated how species occurrence observations vary between different sources and to what extent traditional, citizen science, and social media records are complementary, using the Banded Demoiselle (Calopteryx splendens) in Britain as a case study. Banded Demoiselle occurrences were extracted from citizen science initiatives (iRecord and iNaturalist) and social media platforms (Facebook, Flickr, and Twitter), and compared with traditional records primarily sourced from the British Dragonfly Society. Our results showed that species presence maps differ between record types, with 61% of the citizen science, 58% of the traditional, and 49% of the social media observations being unique to that data type. Banded Demoiselle habitat suitability maps differed most according to traditional and social media projections, with traditional and citizen science being the most consistent. We conclude that (i) social media records provide insights into the Banded Demoiselle distribution and habitat preference that are different from, and complementary to, the insights gathered from traditional recording schemes and citizen science initiatives; (ii) predicted habitat suitability maps that ignore information from social media records can substantially underestimate (by over 3500 km2 in the case of the Banded Demoiselle) potential suitable habitat availability.

Razorbills Alca torda in Italian Seas: A Massive Irruption of Historical Relevance and Role of Social Network Monitoring

Reporting on uncommon wide animal movements could help in depicting potential carry-over effects at the population level, particularly in an era of rapid climate and environmental changes. The razorbill (Alca torda, Linnaeus 1758) is a regular passage migrant and winter visitor to Italian seas, but with sporadic presences usually involving small numbers of individuals. Irruptions have been occasionally documented, with the last records of an unusually large number dating back to 1982. However, in the past, irruptions have only been locally reported and poorly described. Here we report on an unprecedented massive irruption of hundreds of razorbills which occurred in the central Mediterranean Sea in November-December 2022. Using citizen science platforms and photos/videos shared on social networking sites (SNSs), we estimated the relative magnitude of the irruption and described the spatial distribution of birds at sea, as well as report cases of stranded individuals. We collected a total of 267 records, both from Italy and from neighboring countries. We also discuss the likely factors affecting razorbill irruption and stress the importance of open social platforms and data sharing to aid in the early detection and estimation of such events at a wide-scale, as well as for the monitoring of the mortality of the irrupted species.

Big data from a popular app reveals that fishing creates superhighways for aquatic invaders

Human activities are the leading cause of biological invasions that cause ecologic and economic damage around the world. Aquatic invasive species (AIS) are often spread by recreational anglers who visit two or more bodies of water within a short time frame. Movement data from anglers are, therefore, critical to predicting, preventing, and monitoring the spread of AIS. However, the lack of broad-scale movement data has restricted efforts to large and popular lakes or small geographic extents. Here, we show that recreational fishing apps are an abundant, convenient, and relatively comprehensive source of "big" movement data across the contiguous United States. Our analyses revealed a dense network of angler movements that was dramatically more interconnected and extensive than the network that is formed naturally by rivers and streams. Short-distanced movements by anglers combined to form invasion superhighways that spanned the contiguous United States. We also identified possible invasion fronts and invaded hub lakes that may be superspreaders for two relatively common aquatic invaders. Our results provide unique insight into the national network through which AIS may be spread, increase opportunities for interjurisdictional coordination that is essential to addressing the problem of AIS, and highlight the important role that anglers can play in providing accurate data and preventing invasions. The advantages of mobile devices as both sources of data and a means of engaging the public in their shared responsibility to prevent invasions are probably general to all forms of tourism and recreation that contribute to the spread of invasive species.

Addressing the global snakebite crisis with geo-spatial analyses - Recent advances and future direction

Venomous snakebite is a neglected tropical disease that annually leads to hundreds of thousands of deaths or long-term physical and mental ailments across the developing world. Insufficient data on spatial variation in snakebite risk, incidence, human vulnerability, and accessibility of medical treatment contribute substantially to ineffective on-ground management. There is an urgent need to collect data, fill knowledge gaps and address on-ground management problems. The use of novel, and transdisciplinary approaches that take advantage of recent advances in spatio-temporal models, 'big data', high performance computing, and fine-scale spatial information can add value to snakebite management by strategically improving our understanding and mitigation capacity of snakebite. We review the background and recent advances on the topic of snakebite related geospatial analyses and suggest avenues for priority research that will have practical on-ground applications for snakebite management and mitigation. These include streamlined, targeted data collection on snake distributions, snakebites, envenomings, venom composition, health infrastructure, and antivenom accessibility along with fine-scale models of spatio-temporal variation in snakebite risk and incidence, intraspecific venom variation, and environmental change modifying human exposure. These measures could improve and 'future-proof' antivenom production methods, antivenom distribution and stockpiling systems, and human-wildlife conflict management practices, while simultaneously feeding into research on venom evolution, snake taxonomy, ecology, biogeography, and conservation.

Passive citizen science: The role of social media in wildlife observations

Citizen science plays an important role in observing the natural environment. While conventional citizen science consists of organized campaigns to observe a particular phenomenon or species there are also many ad hoc observations of the environment in social media. These data constitute a valuable resource for 'passive citizen science'-the use of social media that are unconnected to any particular citizen science program, but represent an untapped dataset of ecological value. We explore the value of passive citizen science, by evaluating species distributions using the photo sharing site Flickr. The data are evaluated relative to those submitted to the National Biodiversity Network (NBN) Atlas, the largest collection of species distribution data in the UK. Our study focuses on the 1500 best represented species on NBN, and common invasive species within UK, and compares the spatial and temporal distribution with NBN data. We also introduce an innovative image verification technique that uses the Google Cloud Vision API in combination with species taxonomic data to determine the likelihood that a mention of a species on Flickr represents a given species. The spatial and temporal analyses for our case studies suggest that the Flickr dataset best reflects the NBN dataset when considering a purely spatial distribution with no time constraints. The best represented species on Flickr in comparison to NBN are diurnal garden birds as around 70% of the Flickr posts for them are valid observations relative to the NBN. Passive citizen science could offer a rich source of observation data for certain taxonomic groups, and/or as a repository for dedicated projects. Our novel method of validating Flickr records is suited to verifying more extensive collections, including less well-known species, and when used in combination with citizen science projects could offer a platform for accurate identification of species and their location.

iEcology: Harnessing Large Online Resources to Generate Ecological Insights

Digital data are accumulating at unprecedented rates. These contain a lot of information about the natural world, some of which can be used to answer key ecological questions. Here, we introduce iEcology (i.e., internet ecology), an emerging research approach that uses diverse online data sources and methods to generate insights about species distribution over space and time, interactions and dynamics of organisms and their environment, and anthropogenic impacts. We review iEcology data sources and methods, and provide examples of potential research applications. We also outline approaches to reduce potential biases and improve reliability and applicability. As technologies and expertise improve, and costs diminish, iEcology will become an increasingly important means to gain novel insights into the natural world.

Natural history footage provides new reef fish biodiversity information for a pristine but rarely visited archipelago

There remain parts of our planet that are seldom visited by humans, let alone scientists. In such locations, crowd-sourced or citizen scientist data can be critical in describing biodiversity and detecting change. Rangitāhua, the Kermadec Islands, are 750 km from the nearest human-habitation. Although our knowledge of this near pristine location has increased with recent biodiversity expeditions, we still lack comprehensive understanding of the marine biodiversity surrounding the islands. In 2015, professional underwater videographers were commissioned to produce a nature documentary focused on Rangitāhua’s reefs. We strategically surveyed the raw documentary video and examined how biodiversity estimates differed from traditional scientific surveys. We uncovered three new fish species records for Rangitāhua, extending the known distribution for each species, two of which are also new records for New Zealand waters. Comparison of documentary video footage with scientific survey methods showed that estimates of reef fish species richness from the documentary video were similar to stationary surveys, but lower than non-stationary surveys. Moreover, all survey methods, including documentary video, captured different fish assemblages, reflecting each method’s particular bias. Overall, we provide a proof-of-concept for how collaborations between scientists and professional natural historians, such as videographers and photographers, can provide valuable biodiversity information.

Exploring snake occurrence records: Spatial biases and marginal gains from accessible social media

A species' distribution provides fundamental information on: climatic niche, biogeography, and conservation status. Species distribution models often use occurrence records from biodiversity databases, subject to spatial and taxonomic biases. Deficiencies in occurrence data can lead to incomplete species distribution estimates. We can incorporate other data sources to supplement occurrence datasets. The general public is creating (via GPS-enabled cameras to photograph wildlife) incidental occurrence records that may present an opportunity to improve species distribution models. We investigated (1) occurrence data of a cryptic group of animals: non-marine snakes, in a biodiversity database (Global Biodiversity Information Facility (GBIF)) and determined (2) whether incidental occurrence records extracted from geo-tagged social media images (Flickr) could improve distribution models for 18 tropical snake species. We provide R code to search for and extract data from images using Flickr's API. We show the biodiversity database's 302,386 records disproportionately originate from North America, Europe and Oceania (250,063, 82.7%), with substantial gaps in tropical areas that host the highest snake diversity. North America, Europe and Oceania averaged several hundred records per species; whereas Asia, Africa and South America averaged less than 35 per species. Occurrence density showed similar patterns; Asia, Africa and South America have roughly ten-fold fewer records per 100 km2than other regions. Social media provided 44,687 potential records. However, including them in distribution models only marginally impacted niche estimations; niche overlap indices were consistently over 0.9. Similarly, we show negligible differences in Maxent model performance between models trained using GBIF-only and Flickr-supplemented datasets. Model performance appeared dependent on species, rather than number of occurrences or training dataset. We suggest that for tropical snakes, accessible social media currently fails to deliver appreciable benefits for estimating species distributions; but due to the variation between species and the rapid growth in social media data, may still be worth considering in future contexts.

Predicting the timing of ecological phenomena using dates of species occurrence records: a methodological approach and test case with mushrooms

Spatiotemporal predictions of ecological phenomena are highly useful and significant in scientific and socio-economic applications. However, the inadequate availability of ecological time-series data often impedes the development of statistical predictions. On the other hand, considerable amounts of temporally discrete biological records (commonly known as 'species occurrence records') are being stored in public databases, and often include the location and date of the observation. In this paper, we describe an approach to develop spatiotemporal predictions based on the dates and locations found in species occurrence records. The approach is based on 'time-series classification', a field of machine learning, and consists of applying a machine-learning algorithm to classify between time series representing the environmental variation that precedes the occurrence records and time series representing the full range of environmental variation that is available in the location of the records. We exemplify the application of the approach for predicting the timing of emergence of fruiting bodies of two mushroom species (Boletus edulis and Macrolepiota procera) in Europe, from 2009 to 2015. Predictions made from this approach were superior to those provided by a 'null' model representing the average seasonality of the species. Given the increased availability and information contained in species occurrence records, particularly those supplemented with photographs, the range of environmental events that could be possible to predict using this approach is vast.

On the overlap between scientific and societal taxonomic attentions - Insights for conservation

Attention directed at different species by society and science is particularly relevant within the field of conservation, as societal preferences will strongly impact support for conservation initiatives and their success. Here, we assess the association between societal and research interests in four charismatic and threatened species groups, derived from a range of different online sources and social media platforms as well as scientific publications. We found a high level of concordance between scientific and societal taxonomic attention, which was consistent among assessed species groups and media sources. Results indicate that research is apparently not as disconnected from the interests of society as it is often reproached, and that societal support for current research objectives should be adequate. While the high degree of similarity between scientific and societal interest is both striking and satisfying, the dissimilarities are also interesting, as new scientific findings may constitute a constant source of novel interest for the society. In that respect, additional efforts will be necessary to draw scientific and societal focus towards less charismatic species that are in urgent need of research and conservation attention.

Data mining in conservation research using Latin and vernacular species names

In conservation science, assessments of trends and priorities for actions often focus on species as the management unit. Studies on species coverage in online media are commonly conducted by using species vernacular names. However, the use of species vernacular names for web-based data search is problematic due to the high risk of mismatches in results. While the use of Latin names may produce more consistent results, it is uncertain whether a search using Latin names will produce unbiased results as compared to vernacular names. We assessed the potential of Latin names to be used as an alternative to vernacular names for the data mining within the field of conservation science. By using Latin and vernacular names, we searched for species from four species groups: diurnal birds of prey, Carnivora, Primates and marine mammals. We assessed the relationship of the results obtained within different online sources, such as Internet pages, newspapers and social media networks. Results indicated that the search results based on Latin and vernacular names were highly correlated, and confirmed that one may be used as an alternative for the other. We also demonstrated the potential of the number of images posted on the Internet to be used as an indication of the public attention towards different species.

Reuse of scientific data in academic publications

Purpose

– In recent years, a large number of data repositories have been built and used. However, the extent to which scientific data are re-used in academic publications is still unknown. The purpose of this paper is to explore the functions of re-used scientific data in scholarly publication in different fields.

Design/methodology/approach

– To address these questions, the authors identified 827 publications citing resources in the Dryad Digital Repository indexed by Scopus from 2010 to 2015.

Findings

– The results show that: the number of citations to scientific data increases sharply over the years, but mainly from data-intensive disciplines, such as agricultural, biology science, environment science and medicine; the majority of citations are from the originating articles; and researchers tend to reuse data produced by their own research groups.

Research limitations/implications

– Dryad data may be re-used without being formally cited.

Originality/value

– The conservatism in data sharing suggests that more should be done to encourage researchers to re-use other’s data.

Integrating Biodiversity Data into Botanic Collections

BACKGROUND

Today's species names are entry points into a web of publicly available knowledge and are integral parts of legislation concerning biological conservation and consumer safety. Species information usually is fragmented, can be misleading due to the existence of different names and might even be biased because of an identical name that is used for a different species. Safely navigating through the name space is one of the most challenging tasks when associating names with data and when decisions are made which name to include in legislation. Integrating publicly available dynamic data to characterise plant genetic resources of botanic gardens and other facilities will significantly increase the efficiency of recovering relevant information for research projects, identifying potentially invasive taxa, constructing priority lists and developing DNA-based specimen authentication.

NEW INFORMATION

To demonstrate information availability and discuss integration into botanic collections, scientific names derived from botanic gardens were evaluated using the Encyclopedia of Life, The Catalogue of Life and The Plant List. 98.5% of the names could be verified by the combined use of these providers. Comparing taxonomic status information 13 % of the cases were in disagreement. About 7 % of the verified names were found to be included in the International Union for Conservation of Nature Red List, including one extinct taxon and three taxa with the status "extinct in the wild". As second most important factor for biodiversity loss, potential invasiveness was determined. Approximately 4 % of the verified names were detected using the Global Invasive Species Information Network, including 208 invasive taxa. According to Delivering Alien Invasive Species Inventories for Europe around 20 % of the verified names are European alien taxa including 15 of the worst European invasive taxa. Considering alternative names in the data recovery process, success increased up to 18 %.

Figshare: a universal repository for academic resource sharing?

Purpose

– A number of subject-orientated and general websites have emerged to host academic resources. The purpose of this paper is to evaluate the uptake of such services in order to decide which depositing strategies are effective and should be encouraged.

Design/methodology/approach

– This paper evaluates the views and shares of resources in the generic repository Figshare by subject category and resource type.

Findings

– Figshare use and common resource types vary substantially by subject category but resources can be highly viewed even in subjects with few members. More active subject areas do not tend to have more viewed or shared resources.

Research limitations/implications

– The view counts and share counts analysed may reflect author accesses or may be spammed.

Practical implications

– Limited uptake of Figshare within a subject area should not be a barrier to its use. Several highly successful innovative uses for Figshare show that it can reach beyond a purely academic audience.

Originality/value

– This is the first analysis of the uptake and use of a generic academic resource sharing repository.

Digital technology and the conservation of nature

Digital technology is changing nature conservation in increasingly profound ways. We describe this impact and its significance through the concept of 'digital conservation', which we found to comprise five pivotal dimensions: data on nature, data on people, data integration and analysis, communication and experience, and participatory governance. Examining digital innovation in nature conservation and addressing how its development, implementation and diffusion may be steered, we warn against hypes, techno-fix thinking, good news narratives and unverified assumptions. We identify a need for rigorous evaluation, more comprehensive consideration of social exclusion, frameworks for regulation and increased multi-sector as well as multi-discipline awareness and cooperation. Along the way, digital technology may best be reconceptualised by conservationists from something that is either good or bad, to a dual-faced force in need of guidance.

Crowdsourcing the identification of organisms: A case-study of iSpot

Accurate species identification is fundamental to biodiversity science, but the natural history skills required for this are neglected in formal education at all levels. In this paper we describe how the web application ispotnature.org and its sister site ispot.org.za (collectively, “iSpot”) are helping to solve this problem by combining learning technology with crowdsourcing to connect beginners with experts. Over 94% of observations submitted to iSpot receive a determination. External checking of a sample of 3,287 iSpot records verified > 92% of them. To mid 2014, iSpot crowdsourced the identification of 30,000 taxa (>80% at species level) in > 390,000 observations with a global community numbering > 42,000 registered participants. More than half the observations on ispotnature.org were named within an hour of submission. iSpot uses a unique, 9-dimensional reputation system to motivate and reward participants and to verify determinations. Taxon-specific reputation points are earned when a participant proposes an identification that achieves agreement from other participants, weighted by the agreers’ own reputation scores for the taxon. This system is able to discriminate effectively between competing determinations when two or more are proposed for the same observation. In 57% of such cases the reputation system improved the accuracy of the determination, while in the remainder it either improved precision (e.g. by adding a species name to a genus) or revealed false precision, for example where a determination to species level was not supported by the available evidence. We propose that the success of iSpot arises from the structure of its social network that efficiently connects beginners and experts, overcoming the social as well as geographic barriers that normally separate the two.