Response to Horns et al. 2018: ‘Using opportunistic citizen science data to estimate avian population trends’ Biological Conservation 221, 151–159

Fogarty, Frank A.; Wohlfeil, Martha E.; Fleishman, Erica

doi:10.1016/j.biocon.2018.08.005

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…Horns et al 2018a used checklists from a broader scale, the contiguous U.S., to model trends for 574 species, but focused on a shorter timespan (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) when numbers of checklists were high. Horns et al 2018a found trend estimates broadly agreed between eBird and BBS, but there was a large Avian Conservation and Ecology 15(2): 10 http://www.ace-eco.org/vol15/iss2/art10/ variation between species in how well the trends agreed, and many species showed trends with opposite signs (Fogarty et al 2018, Horns et al 2018a. Although both Horns et al 2018a and Walker and Taylor 2017 found that underlying patterns of abundance were captured for many species, refinement of these techniques is necessary to produce reliable population trends using eBird data.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the efficacy of eBird data for modeling historical population trajectories of North American birds and for monitoring populations of boreal and Arctic breeding species

Walker¹,

Taylor²

2020

ACE

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Historic population trajectories for most North American bird species are largely unknown for years prior to circa 1970. Additionally, current estimates of population trajectories of boreal and Arctic breeding species are imprecise or biased because of lack of coverage by Breeding Bird Survey (BBS) routes in that region. Citizen science data, in particular eBird data, could fill these information gaps. Bayesian regression models of eBird data were used to estimate population trajectories of 22 boreal or Arctic breeding species of songbirds, 4 migratory songbird species that breed in eastern North America, and 2 species of raptors whose populations crashed due to the pesticide DDT. Models used range-wide data from the U.S. and Canada for spring migration/breeding, fall migration, and winter. To evaluate the model results, comparisons were made between eBird models from different seasons, between eBird indices and area defoliated by spruce budworm (Choristoneura fumiferana), and between eBird, BBS, and Christmas Bird Count (CBC) annual indices and trends. Population trajectories were positively correlated between seasons for most of the species analyzed based on correlations between annual indices, magnitude of trends, and residuals from trend models. Of the species analyzed, those most often associated with spruce budworm outbreaks had the strongest correlations between eBird annual indices and area defoliated by spruce budworm in the boreal forest. Annual indices from eBird models were positively correlated with BBS for most species, and trends calculated through the annual indices from eBird models were strongly correlated with those from the BBS for spring

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Section: Introductionmentioning

confidence: 99%

Evaluating the efficacy of eBird data for modeling historical population trajectories of North American birds and for monitoring populations of boreal and Arctic breeding species

Walker¹,

Taylor²

2020

ACE

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“…Similarly, Schuttler et al (2019) used camera trap data collected by children as young as 9 years old to obtain reliable mammal species occurrence data near schools in four countries. Horns et al (2018a) determined that estimates of population trends derived from eBird (an online repository for bird count data contributed by amateur birders) records differed little from those based on formal surveys, particularly for widespread species (but see Fogarty, Wohlfeil, & Fleishman, 2018; Horns, Adler, & Şekercioğlu, 2018b).…”

Section: Introductionmentioning

confidence: 99%

Are social media reports useful for assessing small ape occurrence? A pilot study from Peninsular Malaysia

Rameli

Lappan

Bartlett

et al. 2020

American J Primatol

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Citizen science‐based research has been used effectively to estimate animal abundance and breeding patterns, to monitor animal movement, and for biodiversity conservation and education. Here, we evaluate the feasibility of using social media observations to assess the distribution of small apes in Peninsular Malaysia. We searched for reports of small ape observations in Peninsular Malaysia on social media (e.g., blogs, Facebook, Instagram, Twitter, YouTube, iNaturalist, etc.), and also used online, radio, print messaging, and word of mouth to invite citizen scientists such as birders, amateur naturalists, hikers, and other members of the public to provide information about small ape observations made during their activities. These reports provided new information about the occurrence of all three species of small apes (Hylobates agilis, Hylobates lar, and Symphalangus syndactylus) in Peninsular Malaysia. Social media users reported observations of small apes in almost every state. Despite the fact that small apes are believed to occur primarily in the interior of large forested areas, most observations were from fairly small (<100 km2) forests near areas of high traffic and high human population (roads and urban areas). This suggests that most outdoor enthusiasts primarily visit well‐traveled and easily accessible areas, which results in biased sampling if only incidental observations reported on social media are used. A more targeted approach specifically soliciting reports from citizen scientists visiting large, less‐accessible forests may result in better sampling in these habitats. Social media reports indicated the presence of small apes in at least six habitats where they had not been previously reported. We verified the reported data based on whether reports included a date, location, and uploaded photographs, videos and/or audio recordings. Well‐publicized citizen science programs may also build awareness and enthusiasm about the conservation of vulnerable wildlife species.

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Robustness of simple avian population trend models for semi-structured citizen science data is species-dependent

Boersch‐Supan

Trask

Baillie

2019

Biological Conservation

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Response to Horns et al. 2018: ‘Using opportunistic citizen science data to estimate avian population trends’ Biological Conservation 221, 151–159

Cited by 3 publications

References 2 publications

Evaluating the efficacy of eBird data for modeling historical population trajectories of North American birds and for monitoring populations of boreal and Arctic breeding species

Evaluating the efficacy of eBird data for modeling historical population trajectories of North American birds and for monitoring populations of boreal and Arctic breeding species

Are social media reports useful for assessing small ape occurrence? A pilot study from Peninsular Malaysia

Robustness of simple avian population trend models for semi-structured citizen science data is species-dependent

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