Dataset Information

Evaluating firefly extinction risk: Initial red list assessments for North America.

ABSTRACT: Fireflies are a family of charismatic beetles known for their bioluminescent signals. Recent anecdotal reports suggest that firefly populations in North America may be in decline. However, prior to this work, no studies have undertaken a systematic compilation of geographic distribution, habitat specificity, and threats facing North American fireflies. To better understand their extinction risks, we conducted baseline assessments according to the categories and criteria of the International Union for Conservation of Nature (IUCN) Red List for 132 species from the United States and Canada (approximately 79% of described species in the region). We found at least 18 species (14%) are threatened with extinction (e.g. categorized as Critically Endangered, Endangered, or Vulnerable) due to various pressures, including habitat loss, light pollution, and climate change (sea level rise and drought). In addition, more than half of the species (53%) could not be evaluated against the assessment criteria due to insufficient data, highlighting the need for further study. Future research and conservation efforts should prioritize monitoring and protecting populations of at-risk species, preserving and restoring habitat, gathering data on population trends, and filling critical information gaps for data deficient species suspected to be at risk.

SUBMITTER: Fallon CE

PROVIDER: S-EPMC8598072 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Evaluating firefly extinction risk: Initial red list assessments for North America.

Fallon Candace E CE Walker Anna C AC Lewis Sara S Cicero Joseph J Faust Lynn L Heckscher Christopher M CM Pérez-Hernández Cisteil X CX Pfeiffer Ben B Jepsen Sarina S

PloS one 20211117 11

Fireflies are a family of charismatic beetles known for their bioluminescent signals. Recent anecdotal reports suggest that firefly populations in North America may be in decline. However, prior to this work, no studies have undertaken a systematic compilation of geographic distribution, habitat specificity, and threats facing North American fireflies. To better understand their extinction risks, we conducted baseline assessments according to the categories and criteria of the International Unio ...[more]

PMID: 34788329

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Project description:BackgroundThe IUCN Red List of Threatened SpeciesTM (hereafter the Red List) is an important global resource for conservation that supports conservation planning, safeguarding critical habitat and monitoring biodiversity change (Rodrigues et al. 2006). However, a major shortcoming of the Red List is that most of the world's described species have not yet been assessed and published on the Red List (Bachman et al. 2019Eisenhauer et al. 2019). Conservation efforts can be better supported if the Red List is expanded to achieve greater coverage of mega-diverse groups of organisms such as plants, fungi and invertebrates. There is, therefore, an urgent need to speed up the Red List assessment and documentation workflow.One reason for this lack of species coverage is that a manual and relatively time-consuming procedure is usually employed to assess and document species. A recent update of Red List documentation standards (IUCN 2013) reduced the data requirements for publishing non-threatened or 'Least Concern' species on the Red List. The majority of the required fields for Least Concern plant species can be found in existing open-access data sources or can be easily calculated. There is an opportunity to consolidate these data and analyses into a simple application to fast-track the publication of Least Concern assessments for plants. There could be as many as 250,000 species of plants (60%) likely to be categorised as Least Concern (Bachman et al. 2019), for which automatically generated assessments could considerably reduce the outlay of time and valuable resources for Red Listing, allowing attention and resources to be dedicated to the assessment of those species most likely to be threatened.New informationWe present a web application, Rapid Least Concern, that addresses the challenge of accelerating the generation and documentation of Least Concern Red List assessments. Rapid Least Concern utilises open-source datasets, such as the Global Biodiversity Information Facility (GBIF) and Plants of the World Online (POWO) through a simple web interface. Initially, the application is intended for use on plants, but it could be extended to other groups, depending on the availability of equivalent datasets for these groups.Rapid Least Concern users can assess a single species or upload a list of species that are assessed in a batch operation. The batch operation can either utilise georeferenced occurrence data from GBIF or occurrence data provided by the user. The output includes a series of CSV files and a point map file that meet the minimum data requirements for a Least Concern Red List assessment (IUCN 2013). The CSV files are compliant with the IUCN Red List SIS Connect system that transfers the data files to the IUCN database and, pending quality control checks and review, publication on the Red List.We outline the knowledge gap this application aims to fill and describe how the application works. We demonstrate a use-case for Rapid Least Concern as part of an ongoing initiative to complete a global Red List assessment of all native species for the United Kingdom Overseas Territory of Bermuda.

Project description:Assessing the extinction risk of species based on the International Union for Conservation of Nature (IUCN) Red List (RL) is key to guiding conservation policies and reducing biodiversity loss. This process is resource demanding, however, and requires continuous updating, which becomes increasingly difficult as new species are added to the RL. Automatic methods, such as comparative analyses used to predict species RL category, can be an efficient alternative to keep assessments up to date. Using amphibians as a study group, we predicted which species are more likely to change their RL category and thus should be prioritized for reassessment. We used species biological traits, environmental variables, and proxies of climate and land-use change as predictors of RL category. We produced an ensemble prediction of IUCN RL category for each species by combining 4 different model algorithms: cumulative link models, phylogenetic generalized least squares, random forests, and neural networks. By comparing RL categories with the ensemble prediction and accounting for uncertainty among model algorithms, we identified species that should be prioritized for future reassessment based on the mismatch between predicted and observed values. The most important predicting variables across models were species' range size and spatial configuration of the range, biological traits, climate change, and land-use change. We compared our proposed prioritization index and the predicted RL changes with independent IUCN RL reassessments and found high performance of both the prioritization and the predicted directionality of changes in RL categories. Ensemble modeling of RL category is a promising tool for prioritizing species for reassessment while accounting for models' uncertainty. This approach is broadly applicable to all taxa on the IUCN RL and to regional and national assessments and may improve allocation of the limited human and economic resources available to maintain an up-to-date IUCN RL.

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Dataset Information

Evaluating firefly extinction risk: Initial red list assessments for North America.

Publications

Evaluating firefly extinction risk: Initial red list assessments for North America.

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