Assessing adequacy of citizen science datasets for biodiversity monitoring DOI Creative Commons
Louis J. Backstrom, Corey T. Callaghan, Nicholas P. Leseberg

et al.

Ecology and Evolution, Journal Year: 2024, Volume and Issue: 14(2)

Published: Jan. 31, 2024

Tracking the state of biodiversity over time is critical to successful conservation, but conventional monitoring schemes tend be insufficient adequately quantify how species' abundances and distributions are changing. One solution this issue leverage data generated by citizen scientists, who collect vast quantities at temporal spatial scales that cannot matched most traditional methods. However, quality science can vary greatly. In paper, we develop three metrics (inventory completeness, range bias) assess adequacy observation data. We explore species level for Australia's terrestrial native birds then model these against a suite seven traits (threat status, taxonomic uniqueness, body mass, average count, size, density, human population density) identify predictors adequacy. find Australian increasing across two our completeness completeness), not bias, which has worsened time. Relationships between modelled were variable, with only having consistently significant relationships metrics. Our results suggest although generally increased time, there still gaps in many birds. Despite gaps, play an important role providing valuable baseline may supplemented information collected through other believe presented here constitute easily applied approach assessing utility datasets analyses, allowing researchers prioritise regions or lower will benefit from targeted efforts.

Language: Английский

Traits shaping urban tolerance in birds differ around the world DOI Creative Commons
Montague H. C. Neate‐Clegg, Benjamin A. Tonelli, Casey Youngflesh

et al.

Current Biology, Journal Year: 2023, Volume and Issue: 33(9), P. 1677 - 1688.e6

Published: April 5, 2023

As human density increases, biodiversity must increasingly co-exist with urbanization or face local extinction. Tolerance of urban areas has been linked to numerous functional traits, yet few globally consistent patterns have emerged explain variation in tolerance, which stymies attempts at a generalizable predictive framework. Here, we calculate an Urban Association Index (UAI) for 3,768 bird species 137 cities across all permanently inhabited continents. We then assess how this UAI varies as function ten species-specific traits and further test whether the strength trait relationships vary three city-specific variables. Of nine were significantly associated tolerance. Urban-associated tend be smaller, less territorial, greater dispersal ability, broader dietary habitat niches, larger clutch sizes, longevity, lower elevational limits. Only bill shape showed no global association Additionally, several varied latitude and/or population density. For example, associations body mass diet breadth more pronounced higher latitudes, while territoriality longevity reduced Thus, importance filters birds predictably cities, indicating biogeographic selection tolerance that could prior challenges search patterns. A informed framework predicts will integral conservation increasing proportions world's are impacted by urbanization.

Language: Английский

Citations

62
Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers DOI
Mirko Di Febbraro, Luciano Bosso, Mauro Fasola

et al.

Global Change Biology, Journal Year: 2023, Volume and Issue: 29(19), P. 5509 - 5523

Published: Aug. 7, 2023

Abstract Citizen science initiatives have been increasingly used by researchers as a source of occurrence data to model the distribution alien species. Since citizen presence‐only suffer from some fundamental issues, efforts made combine these with those provided scientifically structured surveys. Surprisingly, only few studies proposing integration evaluated contribution this process effective sampling species' environmental niches and, consequently, its effect on predictions new time intervals. We relied niche overlap analyses, machine learning classification algorithms and ecological models compare ability scientific surveys, along their integration, in capturing realized 13 invasive species Italy. Moreover, we assessed differences current future invasion risk predicted each set under multiple global change scenarios. showed that surveys captured similar though highlighting exclusive portions associated clearly identifiable conditions. In terrestrial species, granted highest gain space pooled niches, determining an increased biological risk. A aquatic modelled at regional scale reported net loss compared survey suggesting may also lead contraction niches. For lower These findings indicate represent valuable predicting spread especially within national‐scale programmes. At same time, collected poorly known scientists, or strictly local contexts, strongly affect quantification taxa prediction

Language: Английский

Citations

59
Emerging technologies in citizen science and potential for insect monitoring DOI Creative Commons
Julie Koch Sheard, Tim Adriaens, Diana E. Bowler

et al.

Philosophical Transactions of the Royal Society B Biological Sciences, Journal Year: 2024, Volume and Issue: 379(1904)

Published: May 5, 2024

Emerging technologies are increasingly employed in environmental citizen science projects. This integration offers benefits and opportunities for scientists participants alike. Citizen can support large-scale, long-term monitoring of species occurrences, behaviour interactions. At the same time, foster participant engagement, regardless pre-existing taxonomic expertise or experience, permit new types data to be collected. Yet, may also create challenges by potentially increasing financial costs, necessitating technological demanding training participants. Technology could reduce people's direct involvement engagement with nature. In this perspective, we discuss how current have spurred an increase projects implementation emerging enhance scientific impact public engagement. We show technology act as (i) a facilitator efforts, (ii) enabler research opportunities, (iii) transformer science, policy participation, but become (iv) inhibitor equity rigour. is developing fast promises provide many exciting insect monitoring, while seize these must remain vigilant against potential risks. article part theme issue ‘Towards toolkit global biodiversity monitoring’.

Language: Английский

Citations

16
A comprehensive framework for evaluating ecosystem quality changes and human activity contributions in Inner Mongolia and Xinjiang, China DOI
Faisal Mumtaz, Jing Li, Qinhuo Liu

et al.

Land Use Policy, Journal Year: 2025, Volume and Issue: 151, P. 107494 - 107494

Published: Feb. 5, 2025

Language: Английский

Citations

6
Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes DOI Creative Commons
Ryan M. Carney,

Connor D. Mapes,

Russanne Low

et al.

Insects, Journal Year: 2022, Volume and Issue: 13(8), P. 675 - 675

Published: July 27, 2022

Mosquito-borne diseases continue to ravage humankind with >700 million infections and nearly one deaths every year. Yet only a small percentage of the >3500 mosquito species transmit diseases, necessitating both extensive surveillance precise identification. Unfortunately, such efforts are costly, time-consuming, require entomological expertise. As envisioned by Global Mosquito Alert Consortium, citizen science can provide scalable solution. However, disparate data standards across existing platforms have thus far precluded truly global integration. Here, utilizing Open Geospatial Consortium standards, we harmonized four streams from three established mobile apps—Mosquito Alert, iNaturalist, GLOBE Observer’s Habitat Mapper Land Cover—to facilitate interoperability utility for researchers, control personnel, policymakers. We also launched coordinated media campaigns that generated unprecedented numbers types observations, including successfully capturing first images targeted invasive vector species. Additionally, leveraged pooled image develop toolset artificial intelligence algorithms future deployment in taxonomic anatomical Ultimately, harnessing combined powers intelligence, establish next-generation framework serve as united front combat ongoing threat mosquito-borne worldwide.

Language: Английский

Citations

42
A Double machine learning trend model for citizen science data DOI Creative Commons
Daniel Fink, Alison Johnston, Matthew Strimas‐Mackey

et al.

Methods in Ecology and Evolution, Journal Year: 2023, Volume and Issue: 14(9), P. 2435 - 2448

Published: July 21, 2023

Abstract Citizen and community science datasets are typically collected using flexible protocols. These protocols enable large volumes of data to be globally every year; however, the consequence is that these lack structure necessary maintain consistent sampling across years. This can result in complex pronounced interannual changes observation process, which complicate estimation population trends because over time confounded with process. Here we describe a novel modelling approach designed estimate spatially explicit species while controlling for confounding common citizen data. The based on Double machine learning, statistical framework uses learning (ML) methods change propensity scores used adjust discovered ML makes it possible use sets features control model spatial heterogeneity trends. Additionally, present simulation method identify residual missed by scores. To illustrate approach, estimated from project eBird. We study assess ability varying when faced realistic temporal correlation. Results demonstrated distinguish between constant There were low error rates direction (increasing/decreasing) at each location high correlations magnitude change. accounting inherent has potential fill important information gaps, helping and/or regions lacking rigorous monitoring

Language: Английский

Citations

32
Perspective: sustainability challenges, opportunities and solutions for long-term ecosystem observations DOI Creative Commons
Akira Mori, K. Suzuki, Masakazu Hori

et al.

Philosophical Transactions of the Royal Society B Biological Sciences, Journal Year: 2023, Volume and Issue: 378(1881)

Published: May 29, 2023

As interest in natural capital grows and society increasingly recognizes the value of biodiversity, we must discuss how ecosystem observations to detect changes biodiversity can be sustained through collaboration across regions sectors. However, there are many barriers establishing sustaining large-scale, fine-resolution observations. First, comprehensive monitoring data on both possible anthropogenic factors lacking. Second, some situ cannot systematically established maintained locations. Third, equitable solutions sectors countries needed build a global network. Here, by examining individual cases emerging frameworks, mainly from (but not limited to) Japan, illustrate ecological science relies long-term neglecting basic our home planet further reduces chances overcoming environmental crisis. We also techniques opportunities, such as DNA citizen well using existing forgotten sites monitoring, that help overcome difficulties at large scale with fine resolution. Overall, this paper presents call action for joint factors, systematic establishment maintenance observations, network, beyond cultures, languages, economic status. hope proposed framework examples Japan serve starting point discussions collaborations among stakeholders multiple society. It is time take next step detecting socio-ecological systems, if observation made more feasible, they will play an even important role ensuring sustainability future generations. This article part theme issue 'Detecting attributing causes change: needs, gaps solutions'.

Language: Английский

Citations

29
The data double standard DOI Creative Commons
Allison D. Binley, Joseph Bennett

Methods in Ecology and Evolution, Journal Year: 2023, Volume and Issue: 14(6), P. 1389 - 1397

Published: April 24, 2023

Abstract Conservation planning requires extensive amounts of data, yet data collection is expensive, and there often a trade‐off between the quantity quality that can be collected. Researchers are increasingly turning to community science programs meet their biodiversity needs, reliability such sources still common source debate. Here, we argue professionally collected subject many limitations biases present in datasets. We explore four criticisms comparable issues exist by experts: spatial biases, observer variability, taxonomic misapplication data. then outline solutions these problems have been developed make better use but (and should) equally applied both kinds highlight main based on research using across all research. Statistical techniques for processing help account variation professional Benchmarking or vetting one dataset against another strengthen evidence uncover unknown biases. Professional datasets used together fill knowledge gaps unique each. Careful study design accounts relevant important covariate statistically bias. Currently, double standard exists how researchers view professionals versus those scientists. Our aim ensure valuable given prominent place they deserve, experts appropriately vetted accounted tools at our disposal.

Language: Английский

Citations

23
A modeling framework for biodiversity assessment in renewable energy development: A case study on European bats and wind turbines DOI Creative Commons
Jérémy S. P. Froidevaux, Isabelle Le Viol, Kévin Barré

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 211, P. 115323 - 115323

Published: Jan. 6, 2025

Language: Английский

Citations

1
Avoiding confusion: Modelling image identification surveys with classification errors DOI Creative Commons
Michael A. Spence, Jon Barry,

Thomas Bartos

et al.

Methods in Ecology and Evolution, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 21, 2025

Abstract Automated systems driven by machine learning is becoming increasingly used as an environmental monitoring tool. A common approach to use classification algorithms identify counts of categories (e.g. species) from images. However, the can be biased in presence error. To draw valid conclusions, it crucial incorporate these errors into analysis and interpretation algorithm results. We introduce a general framework for describing with classifiers, including data both classifier confusion matrix. The incorporates uncertainty matrix well generating process. By treating latent variables, our allows wide range processes. illustrate methods three case studies based on simulated different processes, zooplankton Celtic Seas English Channel. widely applicable many subject areas where occur.

Language: Английский

Citations

1