Deriving indicators of biodiversity change from unstructured community-contributed data
About: This article is published in Oikos.The article was published on 2021-06-04. It has received 18 citations till now. The article focuses on the topics: Citizen science.
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TL;DR: The value of List Length Analysis is demonstrated to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia.
Abstract: Long-term systematic population monitoring data sets are rare but are essential in identifying changes in species abundance. In contrast, community groups and natural history organizations have collected many species lists. These represent a large, untapped source of information on changes in abundance but are generally considered of little value. The major problem with using species lists to detect population changes is that the amount of effort used to obtain the list is often uncontrolled and usually unknown. It has been suggested that using the number of species on the list, the "list length," can be a measure of effort. This paper significantly extends the utility of Franklin's approach using Bayesian logistic regression. We demonstrate the value of List Length Analysis to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia. We estimate the magnitude and certainty of change for 269 bird species and calculate the probabilities that there have been declines and increases of given magnitudes. List Length Analysis confirmed suspected species declines and increases. This method is an important complement to systematically designed intensive monitoring schemes and provides a means of utilizing data that may otherwise be deemed useless. The results of List Length Analysis can be used for targeting species of conservation concern for listing purposes or for more intensive monitoring. While Bayesian methods are not essential for List Length Analysis, they can offer more flexibility in interrogating the data and are able to provide a range of parameters that are easy to interpret and can facilitate conservation listing and prioritization. © 2010 by the Ecological Society of America.
97 citations
50 citations
Cites methods from "Deriving indicators of biodiversity..."
...For each user included in the clustering analysis, we calculated the Shannon evenness index (Eobserved; Shannon 1948) on the basis of the proportion of observations in each taxonomic class or each insect order....
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TL;DR: This article investigated 249 youths' contributions to CCS on the iNaturalist platform and found that nearly all the young volunteers' observations were verifiable (included a photo, location, and date/time) and therefore potentially useful to biodiversity research.
Abstract: Online community and citizen science (CCS) projects have broadened access to scientific research and enabled different forms of participation in biodiversity research; however, little is known about whether and how such opportunities are taken up by young people (aged 5–19). Furthermore, when they do participate, there is little research on whether their online activity makes a tangible contribution to scientific research. We addressed these knowledge gaps using quantitative analytical approaches and visualisations to investigate 249 youths’ contributions to CCS on the iNaturalist platform, and the potential for the scientific use of their contributions. We found that nearly all the young volunteers’ observations were ‘verifiable’ (included a photo, location, and date/time) and therefore potentially useful to biodiversity research. Furthermore, more than half were designated as ‘Research Grade’, with a community agreed-upon identification, making them more valuable and accessible to biodiversity science researchers. Our findings show that young volunteers with lasting participation on the platform and those aged 16–19 years are more likely to have a higher proportion of Research Grade observations than younger, or more ephemeral participants. This study enhances our understanding of young volunteers’ contributions to biodiversity research, as well as the important role professional scientists and data users can play in helping verify youths’ contributions to make them more accessible for biodiversity research.
9 citations
Cites methods from "Deriving indicators of biodiversity..."
...These data are then used to build tools to improve management and understand the effects of climate on marine species [39]....
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TL;DR: In this article , the authors compared the opportunistic fish photographs from iNaturalist to those obtained from structured surveys at eight study reefs in Sydney, Australia over twelve years, and found that the latter collected 1.2 to 5.5 times more fish species than the latter.
Abstract: Abstract Citizen science is on the rise, with growing numbers of initiatives, participants and increasing interest from the broader scientific community. iNaturalist is an example of a successful citizen science platform that enables users to opportunistically capture and share biodiversity observations. Understanding how data from such opportunistic citizen science platforms compare with and complement data from structured surveys will improve their use in future biodiversity research. We compared the opportunistic fish photographs from iNaturalist to those obtained from structured surveys at eight study reefs in Sydney, Australia over twelve years. iNaturalist recorded 1.2 to 5.5 times more fish species than structured surveys resulting in significantly greater annual species richness at half of the reefs, with the remainder showing no significant difference. iNaturalist likely recorded more species due to having simple methods, which allowed for broad participation with substantially more iNaturalist observation events (e.g., dives) than structured surveys over the same period. These results demonstrate the value of opportunistic citizen science platforms for documenting fish species richness, particularly where access and use of the marine environment is common and communities have the time and resources for expensive recreational activities (i.e., underwater photography). The datasets also recorded different species composition with iNaturalist recording many rare, less abundant, or cryptic species while the structured surveys captured many common and abundant species. These results suggest that integrating data from both opportunistic and structured data sources is likely to have the best outcome for future biodiversity monitoring and conservation activities.
6 citations
TL;DR: In this paper , the authors examined a large dataset of Australian photographic observations of terrestrial invertebrates uploaded to iNaturalist to quantify recognition to species across different taxa, including dragonflies/damselflies and butterflies.
Abstract: Biodiversity citizen science data are being collected at unprecedented scales, and are key for informing conservation and research. Species-level data typically provide the most valuable information, but recognition of specimens to species level from photographs varies among taxa. We examined a large dataset of Australian photographic observations of terrestrial invertebrates uploaded to iNaturalist to quantify recognition to species across different taxa. We also quantified the proportion of Australian species that have been uploaded to iNaturalist. Across 1,013,171 observations covering 14,663 species (17.8% completeness), 617,045 (60.9%) were recognized to species. Dragonflies/damselflies and butterflies were the best-recognized and most complete taxa, and therefore represent the best groups for researchers and managers intending to use existing iNaturalist data at large spatial and temporal scales. The recruitment of additional experts to identify records, and enhanced support for accessible resources for hard-to-identify taxa, will likely increase recognition for other taxa.
3 citations
References
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TL;DR: It is shown that a wide variety of vertebrate and invertebrate species have moved northwards and uphill in Britain over approximately 25 years, mirroring, and in some cases exceeding, the responses of better‐known groups.
Abstract: Evidence is accumulating of shifts in species' distributions during recent climate warming. However, most of this information comes predominantly from studies of a relatively small selection of taxa (i.e., plants, birds and butterflies), which may not be representative of biodiversity as a whole. Using data from less well-studied groups, we show that a wide variety of vertebrate and invertebrate species have moved northwards and uphill in Britain over approximately 25 years, mirroring, and in some cases exceeding, the responses of better-known groups.
1,392 citations
TL;DR: The dual forces of habitat modification and climate change are likely to cause specialists to decline, leaving biological communities with reduced numbers of species and dominated by mobile and widespread habitat generalists.
Abstract: Habitat degradation and climate change are thought to be altering the distributions and abundances of animals and plants throughout the world, but their combined impacts have not been assessed for any species assemblage1,2,3,4. Here we evaluated changes in the distribution sizes and abundances of 46 species of butterflies that approach their northern climatic range margins in Britain—where changes in climate and habitat are opposing forces. These insects might be expected to have responded positively to climate warming over the past 30 years, yet three-quarters of them declined: negative responses to habitat loss have outweighed positive responses to climate warming. Half of the species that were mobile and habitat generalists increased their distribution sites over this period (consistent with a climate explanation), whereas the other generalists and 89% of the habitat specialists declined in distribution size (consistent with habitat limitation). Changes in population abundances closely matched changes in distributions. The dual forces of habitat modification and climate change are likely to cause specialists to decline, leaving biological communities with reduced numbers of species and dominated by mobile and widespread habitat generalists.
1,273 citations
TL;DR: Citizen science and the resulting ecological data can be viewed as a public good that is generated through increasingly collaborative tools and resources, while supporting public participation in science and Earth stewardship as discussed by the authors.
Abstract: Approaches to citizen science – an indispensable means of combining ecological research with environmental education and natural history observation – range from community-based monitoring to the use of the internet to “crowd-source” various scientific tasks, from data collection to discovery. With new tools and mechanisms for engaging learners, citizen science pushes the envelope of what ecologists can achieve, both in expanding the potential for spatial ecology research and in supplementing existing, but localized, research programs. The primary impacts of citizen science are seen in biological studies of global climate change, including analyses of phenology, landscape ecology, and macro-ecology, as well as in sub-disciplines focused on species (rare and invasive), disease, populations, communities, and ecosystems. Citizen science and the resulting ecological data can be viewed as a public good that is generated through increasingly collaborative tools and resources, while supporting public participation in science and Earth stewardship.
1,097 citations
University of Lisbon1, Commonwealth Scientific and Industrial Research Organisation2, Virginia Tech College of Natural Resources and Environment3, California Institute of Technology4, Wageningen University and Research Centre5, Cardiff University6, American Museum of Natural History7, BirdLife International8, University of British Columbia9, Food and Agriculture Organization10, Australian Museum11, Leibniz Association12, Royal Society for the Protection of Birds13, University of Maryland, College Park14, Yale University15, Stanford University16, Monash University17, Kyoto University18, Zoological Society of London19, United States Geological Survey20, United Nations Environment Programme21, University of Sussex22, International Union for Conservation of Nature and Natural Resources23, Office of Environment and Heritage24
TL;DR: With the first plenary meeting of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) soon under way, partners are developing—and seeking consensus around—Essential Biod diversity Variables (EBVs) that could form the basis of monitoring programs worldwide.
Abstract: Reducing the rate of biodiversity loss and averting dangerous biodiversity change are international goals, reasserted by the Aichi Targets for 2020 by Parties to the United Nations (UN) Convention on Biological Diversity (CBD) after failure to meet the 2010 target (1, 2). However, there is no global, harmonized observation system for delivering regular, timely data on biodiversity change (3). With the first plenary meeting of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) soon under way, partners from the Group on Earth Observations Biodiversity Observation Network (GEO BON) (4) are developing—and seeking consensus around—Essential Biodiversity Variables (EBVs) that could form the basis of monitoring programs worldwide.
1,074 citations
TL;DR: This work provides a worked example of spatial thinning of species occurrence records for the Caribbean spiny pocket mouse, where the results obtained match those of manual thinning.
Abstract: Spatial thinning of species occurrence records can help address problems associated with spatial sampling biases. Ideally, thinning removes the fewest records necessary to substantially reduce the effects of sampling bias, while simultaneously retaining the greatest amount of useful information. Spatial thinning can be done manually; however, this is prohibitively time consuming for large datasets. Using a randomization approach, the ‘thin’ function in the spThin R package returns a dataset with the maximum number of records for a given thinning distance, when run for sufficient iterations. We here provide a worked example for the Caribbean spiny pocket mouse, where the results obtained match those of manual thinning.
1,016 citations