Citizen science and online data: Opportunities and challenges for snake ecology and action against snakebite

A review of age estimation methods in non-avian reptiles by growth marks in hard tissues

Age and growth-related data are basic biological parameters, essential in population ecology, evolution, and conservation biology. There is a growing body of published information on reptile demography derived from sclerochronology, a technique based on counting the growth layers deposited in bones (skeletochronology) and other hard body structures. Since the data are not always easily available, we compiled the existing published data, described the current status of knowledge, synthetized the conclusions of disparate studies, and identified patterns of research and information gaps, prioritizing the needs for future research. Our database includes the results of 468 published studies covering 236 reptile species from 41 families. These represent less than 2% of the total number of known extant species. Turtles and crocodiles are proportionally better studied, while snakes are the least examined group. The distribution of the research does not reflect conservation needs; we found an important geographic bias, with an overrepresentation of Northern temperate species. Only 23% of the studies checked the assumption of periodicity of growth marks deposition, and the method was found to be reliable or adequate in 79% of the cases. Overall, the data obtained through sclerochronology can be considered robust, especially if validation methods are employed, since the general goal is to characterize population parameters, trends, and dynamics, rather than determining the exact age of any specimen in particular.

Quantifying error in occurrence data: Comparing the data quality of iNaturalist and digitized herbarium specimen data in flowering plant families of the southeastern United States

iNaturalist has the potential to be an extremely rich source of organismal occurrence data. Launched in 2008, it now contains over 150 million uploaded observations as of May 2023. Based on the findings of a limited number of past studies assessing the taxonomic accuracy of participatory science-driven sources of occurrence data such as iNaturalist, there has been concern that some portion of these records might be misidentified in certain taxonomic groups. In this case study, we compare Research Grade iNaturalist observations with digitized herbarium specimens, both of which are currently available for combined download from large data aggregators and are therefore the primary sources of occurrence data for large-scale biodiversity/biogeography studies. Our comparisons were confined regionally to the southeastern United States (Florida, Georgia, North Carolina, South Carolina, Texas, Tennessee, Kentucky, and Virginia). Occurrence records from ten plant families (Gentianaceae, Ericaceae, Melanthiaceae, Ulmaceae, Fabaceae, Asteraceae, Fagaceae, Cyperaceae, Juglandaceae, Apocynaceae) were downloaded and scored on taxonomic accuracy. We found a comparable and relatively low rate of misidentification among both digitized herbarium specimens and Research Grade iNaturalist observations within the study area. This finding illustrates the utility and high quality of iNaturalist data for future research in the region, but also points to key differences between data types, giving each a respective advantage, depending on applications of the data.

Identifying high snakebite risk area under climate change for community education and antivenom distribution

Snakebite is one of the largest risks from wildlife, however little is known about venomous snake distribution, spatial variation in snakebite risk, potential changes in snakebite risk pattern due to climate change, and vulnerable human population. As a consequence, management and prevention of snakebite is hampered by this lack of information. Here we used habitat suitability modeling for 10 medically important venomous snakes to identify high snakebite risk area under climate change in Iran. We identified areas with high snakebite risk in Iran and showed that snakebite risk will increase in some parts of the country. Our results also revealed that mountainous areas (Zagros, Alborz, Kopet-Dagh mountains) will experience highest changes in species composition. We underline that in order to improve snakebite management, areas which were identified with high snakebite risk in Iran need to be prioritized for the distribution of antivenom medication and awareness rising programs among vulnerable human population.

An artificial intelligence model to identify snakes from across the world: Opportunities and challenges for global health and herpetology

Background

Snakebite envenoming is a neglected tropical disease that kills an estimated 81,000 to 138,000 people and disables another 400,000 globally every year. The World Health Organization aims to halve this burden by 2030. To achieve this ambitious goal, we need to close the data gap in snake ecology and snakebite epidemiology and give healthcare providers up-to-date knowledge and access to better diagnostic tools. An essential first step is to improve the capacity to identify biting snakes taxonomically. The existence of AI-based identification tools for other animals offers an innovative opportunity to apply machine learning to snake identification and snakebite envenoming, a life-threatening situation.

Methodology

We developed an AI model based on Vision Transformer, a recent neural network architecture, and a comprehensive snake photo dataset of 386,006 training photos covering 198 venomous and 574 non-venomous snake species from 188 countries. We gathered photos from online biodiversity platforms (iNaturalist and HerpMapper) and a photo-sharing site (Flickr).

Principal findings

The model macro-averaged F1 score, which reflects the species-wise performance as averaging performance for each species, is 92.2%. The accuracy on a species and genus level is 96.0% and 99.0%, respectively. The average accuracy per country is 94.2%. The model accurately classifies selected venomous and non-venomous lookalike species from Southeast Asia and sub-Saharan Africa.

Conclusions

To our knowledge, this model’s taxonomic and geographic coverage and performance are unprecedented. This model could provide high-speed and low-cost snake identification to support snakebite victims and healthcare providers in low-resource settings, as well as zoologists, conservationists, and nature lovers from across the world.

Revisiting the potential of South American rattlesnake Crotalus durissus terrificus toxins as therapeutic, theranostic and/or biotechnological agents

The potential biotechnological and biomedical applications of the animal venom components are widely recognized. Indeed, many components have been used either as drugs or as templates/prototypes for the development of innovative pharmaceutical drugs, among which many are still used for the treatment of human diseases. A specific South American rattlesnake, named Crotalus durissus terrificus, shows a venom composition relatively simpler compared to any viper or other snake species belonging to the Crotalus genus, although presenting a set of toxins with high potential for the treatment of several still unmet human therapeutic needs, as reviewed in this work. In addition to the main toxin named crotoxin, which is under clinical trials studies for antitumoral therapy and which has also anti-inflammatory and immunosuppressive activities, other toxins from the C. d. terrificus venom are also being studied, aiming for a wide variety of therapeutic applications, including as antinociceptive, anti-inflammatory, antimicrobial, antifungal, antitumoral or antiparasitic agent, or as modulator of animal metabolism, fibrin sealant (fibrin glue), gene carrier or theranostic agent. Among these rattlesnake toxins, the most relevant, considering the potential clinical applications, are crotamine, crotalphine and gyroxin. In this narrative revision, we propose to organize and present briefly the updates in the accumulated knowledge on potential therapeutic applications of toxins collectively found exclusively in the venom of this specific South American rattlesnake, with the objective of contributing to increase the chances of success in the discovery of drugs based on toxins.

Web-based snake identification service: A successful model of snake identification in Sri Lanka

Snakes are reptiles of great biomedical significance. The accurate identification of snakes is particularly important for healthcare workers to diagnose and treat victims of snakebite envenoming. Further, snake identification is vital for the general population, especially to those who live in areas of high snakebite incidence. Owing to the great diversity of snakes and the superficial similarities between some species, the correct identification of these reptiles is often difficult. Therefore, identification of snake species is challenging for healthcare workers, biologists, naturalists, and the general population. To overcome this challenge, we developed a web-based snake identification service (www.snakesidentification.org) in Sri Lanka, which provides rapid and accurate identification by experienced herpetologists. This service received 486 identification requests over a period of 40 months. The majority of requests were from Colombo District [140 (28.8%)], though only 63 (13.0%) of these were identified as medically important snakes. The majority [389 (80.0%)] of the requests related either to feebly venomous colubrid snakes or non-venomous species. The sample included 30 (of 107) snake species in the island, including 8 endemic species. There were 315 (64.8%) requests relating to live snakes. In the majority of cases (285, 90.4%), the snake was released to the closest available habitat after being identified. The median time taken to respond to requests was 70 min (interquartile range 23-299 min). The majority of persons making requests (283, 58.2%) were unable to identify the snakes. For those who attempted identification the snakes, correct identification was made by only 59 (12.1%), whereas 144 (29.6%) identified the snake incorrectly. This web-based snake identification service provides an example of a successful and useful model of rapid snake identification. Similar models could be implemented in other regions and countries to provide accurate information on snake identification both to the healthcare workers and the general public.