scholarly journals Notes of Life: A platform for recording species observations driven by artificial intelligence

2019 ◽  
Vol 3 ◽  
Author(s):  
Congtian Lin ◽  
Jiangning Wang ◽  
Liqiang Ji
Keyword(s):  
Artificial Intelligence ◽  
Citizen Science ◽  
Higher Plants ◽  
Mobile App ◽  
Biodiversity Data ◽  
Science Data ◽  
Biodiversity Research ◽  
Large Numbers ◽  
In The Wild ◽  
Speed Up

Biodiversity research is stepping into a big data era with the rapid increase in the abundance of biodiversity data, especially the large number of species images. It has been a new trend and hot topic on how to utilize artificial intelligence to mine big biodiversity data to support wildlife observation and recognition. In this research, we integrate large numbers of species images, including higher plants, birds and insects, and use a state-of-the-art image deep learning technique to train species auto-recognition models. Currently, we get a model that can recognize more than 900 Chinese birds with top 1 accuracy 81% and top 5 accuracy 95% (top n accuracy means the probability that the correct answer presents in top n predicted results), and more models are coming soon. Based on these models, we developed a platform named Notes of Life (NOL, http://nol.especies.cn), which includes a website and a mobile application (app) for assisting biological scientists and citizen scientists to recognize and record wildlife. Users can upload their observation records and images of wildlife through our mobile app while they are investigating in the wild. The website is used for bulk data uploading and management. Species images can be classified by taxon-specific, plug-in recognition models that speed up the process of identification. There is an expert module in NOL where citizen scientists can work interactively with information provided by biological scientists, and post a species image identification request to experts when they cannot recognize the species by themselves or from models. The expert module is for improving the quality of citizen science data, and it is a supplement of the disadvantage of species auto-recognition models. Above all, NOL embraces the idea that scientific research supports citizen science and citizen science gives feedback to science, and of finding a sustainable way to collect increasingly more reliable data for biodiversity research.

Three Frontiers for the Future of Biodiversity Research Using Citizen Science Data

BioScience ◽  
2020 ◽  
Author(s):  
Corey T Callaghan ◽  
Alistair G B Poore ◽  
Thomas Mesaglio ◽  
Angela T Moles ◽  
Shinichi Nakagawa ◽  
...  
Keyword(s):  
Citizen Science ◽  
Secondary Data ◽  
Science Research ◽  
Single Species ◽  
Data Sets ◽  
Biodiversity Data ◽  
Science Data ◽  
Biodiversity Research ◽  
Research Areas ◽  
The Future

Abstract Citizen science is fundamentally shifting the future of biodiversity research. But although citizen science observations are contributing an increasingly large proportion of biodiversity data, they only feature in a relatively small percentage of research papers on biodiversity. We provide our perspective on three frontiers of citizen science research, areas that we feel to date have had minimal scientific exploration but that we believe deserve greater attention as they present substantial opportunities for the future of biodiversity research: sampling the undersampled, capitalizing on citizen science's unique ability to sample poorly sampled taxa and regions of the world, reducing taxonomic and spatial biases in global biodiversity data sets; estimating abundance and density in space and time, develop techniques to derive taxon-specific densities from presence or absence and presence-only data; and capitalizing on secondary data collection, moving beyond data on the occurrence of single species and gain further understanding of ecological interactions among species or habitats. The contribution of citizen science to understanding the important biodiversity questions of our time should be more fully realized.

scholarly journals A Framework of Observer-Based Biases in Citizen Science Biodiversity Monitoring: Semi-Structuring Unstructured Biodiversity Monitoring Protocols

2021 ◽  
Vol 9 ◽  
Author(s):  
Ofer Arazy ◽  
Dan Malkinson
Keyword(s):  
Decision Making ◽  
Citizen Science ◽  
Temporal Distribution ◽  
Biodiversity Monitoring ◽  
Biodiversity Data ◽  
Science Data ◽  
The Public ◽  
Spatio Temporal ◽  
Monitoring Protocols ◽  
And Behavior

Citizen science, whereby ordinary citizens participate in scientific endeavors, is widely used for biodiversity monitoring, most commonly by relying on unstructured monitoring approaches. Notwithstanding the potential of unstructured citizen science to engage the public and collect large amounts of biodiversity data, observers’ considerations regarding what, where and when to monitor result in biases in the aggregate database, thus impeding the ability to draw conclusions about trends in species’ spatio-temporal distribution. Hence, the goal of this study is to enhance our understanding of observer-based biases in citizen science for biodiversity monitoring. Toward this goals we: (a) develop a conceptual framework of observers’ decision-making process along the steps of monitor – > record and share, identifying the considerations that take place at each step, specifically highlighting the factors that influence the decisions of whether to record an observation (b) propose an approach for operationalizing the framework using a targeted and focused questionnaire, which gauges observers’ preferences and behavior throughout the decision-making steps, and (c) illustrate the questionnaire’s ability to capture the factors driving observer-based biases by employing data from a local project on the iNaturalist platform. Our discussion highlights the paper’s theoretical contributions and proposes ways in which our approach for semi-structuring unstructured citizen science data could be used to mitigate observer-based biases, potentially making the collected biodiversity data usable for scientific and regulatory purposes.

scholarly journals Tipulodes annae Przybyłowicz, 2003 (Lepidoptera, Erebidae), citizen science and its rediscovery in the wild.

Check List ◽  
2021 ◽  
Vol 17 (5) ◽  
pp. 1255-1259
Author(s):  
Julian Alzate Cano ◽  
Edwin Alejandro Hurtado Pimienta
Keyword(s):  
Citizen Science ◽  
First Record ◽  
Biodiversity Research ◽  
In The Wild

We report here the rediscovery of Tipulodes annae Przybyłowicz, 2003 (Erebidae, Arctiinae), which was originally collected in 1924 and has been unseen and not collected in 84 years, until 2008. We also report this species’ first record in Panama and additional localities in Colombia using citizen science platforms. This data is useful information for the conservation of this small moth, and it highlights the importance and utility of citizen science platforms in biodiversity research.

scholarly journals Experiences from the Danish Fungal Atlas: Linking mushrooming, nature conservation and primary biodiversity research 

2021 ◽  
Vol 5 ◽  
Author(s):  
Jacob Heilmann-Clausen ◽  
Tobias Frøslev ◽  
Jens Petersen ◽  
Thomas Læssøe ◽  
Thomas Jeppesen
Keyword(s):  
Nature Conservation ◽  
Dna Sequencing ◽  
Citizen Science ◽  
High Throughput Sequencing ◽  
Low Cost ◽  
Mobile App ◽  
Science Data ◽  
Global Biodiversity Information Facility ◽  
Validation Data ◽  
Species Discovery

The Danish Fungal Atlas is a citizen science project launched in 2009 in collaboration among the University of Copenhagen, Mycokey and the Danish Mycological Society. The associated database now holds almost 1 million fungal records, contributed by more than 3000 recorders. The records represent more than 8000 fungal species, of which several hundred have been recorded as new to Denmark during the project. In addition several species have been described as new to science. Data are syncronized with the Global Biodiversity Information Facility (GBIF) on a weekly basis, and is hence freely available for research and nature conservation. Data have been used for systematic conservation planning in Denmark, and several research papers have used data to explore subjects such as host selection in wood-inhabiting fungi (Heilmann‐Clausen et al. 2016), recording bias in citizen science (Geldmann et al. 2016), fungal traits (Krah et al. 2019), biodiversity patterns (e.g. Andrew et al. 2018), and species discovery (Heilmann-Clausen et al. 2019). The project database is designed to faciliate direct interactions and communication among volunteers. The validation of submitted records is interactive and combines species-specific smart filters, user credibility, and expert tools to secure the highest possible data credibility. In 2019, an AI (artificial intelligence) trained species identification tool was launched along with a new mobile app, enabling users to identify and record species directly in the field (Sulc et al. 2020). At the same time, DNA sequencing was tested as an option to test difficult identifications, and in 2021 a high-throughput sequencing facility was developed to allow DNA sequencing of hundreds of fungal collections at a low cost. The presentation will give details on data validation, data use and how we have worked with cultivation of volunteers to provide a truly coherent model for collaboration on mushroom citizen science.

Estimating hybridization in the wild using citizen science data: a path forward

Evolution ◽  
2021 ◽  
Author(s):  
Nicholas R. Minor ◽  
Paul J. Dougherty ◽  
Scott A. Taylor ◽  
Matthew D. Carling
Keyword(s):  
Citizen Science ◽  
Science Data ◽  
In The Wild

scholarly journals Using iNaturalist to Contribute Your Nature Observations to Science

EDIS ◽  
2019 ◽  
Vol 2019 (4) ◽  
pp. 5
Author(s):  
Matthew Earl Boone ◽  
Mathieu Basille
Keyword(s):  
Citizen Science ◽  
Online Community ◽  
Science Data ◽  
Online Data ◽  
Wildlife Ecology ◽  
Biodiversity Research ◽  
The World ◽  
The Rich ◽  
Online Data Base ◽  
Community Projects

iNaturalist is one of the most popular citizen science data portals in the world. Citizens can submit pictures of biological observations to an online data base to be reviewed by the rich online community and used for important biodiversity research around the world. Users can use the iNaturalist ap to plan community projects and bioblitzes and learn more about species identification and biodiversity. In this 5-page fact sheet, authors Matthew Earl Boone and Mathieu Basille explain how observations are vetted and used and give a step by step guide to get started! Published by the UF/IFAS Department of Wildlife Ecology and Conservation. https://edis.ifas.ufl.edu/uw458

scholarly journals The Use of Citizen Science to Achieve Multivariate Management Goals on Public Lands

Diversity ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 293
Author(s):  
Sara Souther ◽  
Vincent Randall ◽  
Nanebah Lyndon
Keyword(s):  
Citizen Science ◽  
Land Management ◽  
Ecological Integrity ◽  
Public Land ◽  
Suitable Habitat ◽  
Science Data ◽  
Public Land Management ◽  
Federal Land ◽  
Botanical Research ◽  
Federal Land Management

Federal land management agencies in the US are tasked with maintaining the ecological integrity of over 2 million km2 of land for myriad public uses. Citizen science, operating at the nexus of science, education, and outreach, offers unique benefits to address socio-ecological questions and problems, and thus may offer novel opportunities to support the complex mission of public land managers. Here, we use a case study of an iNaturalist program, the Tribal Nations Botanical Research Collaborative (TNBRC), to examine the use of citizen science programs in public land management. The TNBRC collected 2030 observations of 34 plant species across the project area, while offering learning opportunities for participants. Using occurrence data, we examined observational trends through time and identified five species with 50 or fewer digital observations to investigate as species of possible conservation concern. We compared predictive outcomes of habitat suitability models built using citizen science data and Forest Inventory and Analysis (FIA) data. Models exhibited high agreement, identifying the same underlying predictors of species occurrence and, 95% of the time, identifying the same pixels as suitable habitat. Actions such as staff training on data use and interpretation could enhance integration of citizen science in Federal land management.

scholarly journals The environmental and ecological determinants of elevated Ross River Virus exposure in koalas residing in urban coastal landscapes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Brian J. Johnson ◽  
Amy Robbins ◽  
Narayan Gyawali ◽  
Oselyne Ong ◽  
Joanne Loader ◽  
...  
Keyword(s):  
Animal Movement ◽  
Ross River Virus ◽  
Mosquito Vector ◽  
Large Numbers ◽  
Culex Annulirostris ◽  
Coastal Landscapes ◽  
In The Wild ◽  
Virus Exposure ◽  
Elevated Exposure ◽  
The Impact

AbstractKoala populations in many areas of Australia have declined sharply in response to habitat loss, disease and the effects of climate change. Koalas may face further morbidity from endemic mosquito-borne viruses, but the impact of such viruses is currently unknown. Few seroprevalence studies in the wild exist and little is known of the determinants of exposure. Here, we exploited a large, spatially and temporally explicit koala survey to define the intensity of Ross River Virus (RRV) exposure in koalas residing in urban coastal environments in southeast Queensland, Australia. We demonstrate that RRV exposure in koalas is much higher (> 80%) than reported in other sero-surveys and that exposure is uniform across the urban coastal landscape. Uniformity in exposure is related to the presence of the major RRV mosquito vector, Culex annulirostris, and similarities in animal movement, tree use, and age-dependent increases in exposure risk. Elevated exposure ultimately appears to result from the confinement of remaining coastal koala habitat to the edges of permanent wetlands unsuitable for urban development and which produce large numbers of competent mosquito vectors. The results further illustrate that koalas and other RRV-susceptible vertebrates may serve as useful sentinels of human urban exposure in endemic areas.

scholarly journals Abundant Citizen Science Data Reveal That the Peacock Butterfly Aglais io Recently Became Bivoltine in Belgium

Insects ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 683
Author(s):  
Marc Herremans ◽  
Karin Gielen ◽  
Jos Van Kerckhoven ◽  
Pieter Vanormelingen ◽  
Wim Veraghtert ◽  
...  
Keyword(s):  
Citizen Science ◽  
Western Europe ◽  
Environmental Changes ◽  
Early Summer ◽  
Science Data ◽  
The Public ◽  
Online Portal ◽  
Spring Generation ◽  
Reproductive Cycles ◽  
New Generation

The peacock butterfly is abundant and widespread in Europe. It is generally believed to be univoltine (one generation per year): adults born in summer overwinter and reappear again in spring to reproduce. However, recent flight patterns in western Europe mostly show three peaks during the year: a first one in spring (overwintering butterflies), a second one in early summer (offspring of the spring generation), and a third one in autumn. It was thus far unclear whether this autumn flight peak was a second new generation or consisted of butterflies flying again in autumn after a summer rest (aestivation). The life cycle of one of Europe’s most common butterflies is therefore still surprisingly inadequately understood. We used hundreds of thousands of observations and thousands of pictures submitted by naturalists from the public to the online portal observation.orgin Belgium and analyzed relations between flight patterns, condition (wear), reproductive cycles, peak abundances, and phenology to clarify the current life history. We demonstrate that peacocks have shifted towards two new generations per year in recent decades. Mass citizen science data in online portals has become increasingly important in tracking the response of biodiversity to rapid environmental changes such as climate change.

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