The potential for citizen science to produce reliable and useful information in ecology

Brown, Eleanor D.; Williams, Byron K.

doi:10.1111/cobi.13223

Cited by 131 publications

(127 citation statements)

References 65 publications

(216 reference statements)

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“…Thus, the development of approaches to combine systematic surveys with incidental sightings data would be desirable, as sightings can confirm species presence in areas where systematic surveys are not conducted or feasible. In particular, statistically robust analytical methods or the use of external data need to be considered to increase the inferential validity of model-based population estimates derived from incidentally or opportunistically collected wildlife data 27 . Some recent research has described methodologies for combing sightings data with systematic survey data to estimate the density of wildlife species 26,43 .…”

Section: Discussionmentioning

confidence: 99%

“…Data obtained through the Frogwatch program, for example, are used by scientists to time surveys and to identify sampling sites to increase the probability of detection. While having the potential to provide a cost effective approach for documenting wildlife presence or absence appropriate adjustments need to be made to accumulated data to allow appropriate inferences to be made at the population level, in particular if chance observations are recorded without a specific sampling design 24–27 .…”

Section: Introductionmentioning

confidence: 99%

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The value of long-term citizen science data for monitoring koala populations

Dissanayake

Stevenson

Allavena

et al. 2019

Sci Rep

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The active collection of wildlife sighting data by trained observers is expensive, restricted to small geographical areas and conducted infrequently. Reporting of wildlife sightings by members of the public provides an opportunity to collect wildlife data continuously over wider geographical areas, at lower cost. We used individual koala sightings reported by members of the public between 1997 and 2013 in South-East Queensland, Australia ( n = 14,076 koala sightings) to describe spatial and temporal trends in koala presence, to estimate koala sighting density and to identify biases associated with sightings. Temporal trends in sightings mirrored the breeding season of koalas. Sightings were high in residential areas (63%), followed by agricultural (15%), and parkland (12%). The study area was divided into 57,780 one-square kilometer grid cells and grid cells with no sightings of koalas decreased over time (from 35% to 21%) indicative of a greater level of spatial overlap of koala home ranges and human activity areas over time. The density of reported koala sightings decreased as distance from primary and secondary roads increased, indicative of a higher search effort near roads. Our results show that koala sighting data can be used to refine koala distribution and population estimates derived from active surveying, on the condition that appropriate bias correction techniques are applied. Collecting koala absence and search effort information and conducting repeated searches for koalas in the same areas are useful approaches to improve the quality of sighting data in citizen science programs.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The value of long-term citizen science data for monitoring koala populations

Dissanayake

Stevenson

Allavena

et al. 2019

Sci Rep

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“…While the results illustrate that we can learn much from the tagging data, these data have their limitations. Some of these limitations affect particular measures and interpretations relevant to the monarch migration; others are problems common to most citizen science projects (Brown and Williams, 2019). Although tags failing to adhere to monarch wings and effects of handling while tagging are thought to be minimal, both values could affect the results by increasing mortality during the migration and perhaps during the winter period.…”

Section: Is Timing Of the Migration Related To Overwintering Monarch mentioning

confidence: 99%

Is the Timing, Pace, and Success of the Monarch Migration Associated With Sun Angle?

et al. 2019

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A basic question concerning the monarch butterflies' fall migration is which monarchs succeed in reaching overwintering sites in Mexico, which fail-and why. We document the timing and pace of the fall migration, ask whether the sun's position in the sky is associated with the pace of the migration, and ask whether timing affects success in completing the migration. Using data from the Monarch Watch tagging program, we explore whether the fall monarch migration is associated with the daily maximum vertical angle of the sun above the horizon (Sun Angle at Solar Noon, SASN) or whether other processes are more likely to explain the pace of the migration. From 1998 to 2015, more than 1.38 million monarchs were tagged and 13,824 (1%) were recovered in Mexico. The pace of migration was relatively slow early in the migration but increased in late September and declined again later in October as the migrating monarchs approached lower latitudes. This slow-fast-slow pacing in the fall migration is consistent with monarchs reaching latitudes with the same SASN, day after day, as they move south to their overwintering sites. The observed pacing pattern and overall movement rates are also consistent with monarchs migrating at a pace determined by interactions among SASN, temperature, and daylength. The results suggest monarchs successfully reaching the Monarch Butterfly Biosphere Reserve (MBBR) migrate within a "migration window" with an SASN of about 57 • at the leading edge of the migration and 46 • at the trailing edge. Ninety percent of the tags recovered in Mexico were from monarchs tagged within this window. Migrants reaching locations along the migration route with SASN outside this migration window may be considered early or late migrants. We noted several years with low overwintering abundance of monarchs, 2004 and 2011-2014, with high percentages of late migrants. This observation suggests a possible effect of migration timing on population size. The migration window defined by SASN can serve as a framework against which to establish the influence of environmental factors on the size, geographic distribution, and timing of past and future fall migrations.

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“…This was due to an inability to account for the numerous sources of bias introduced from unstructured data for example, reporting bias toward certain popular species. In general, the usefulness of passive surveillance data in plant health will increase for structured or semi-structured schemes where sources of bias can be accounted (for example Brown and Williams 2019 ). However, data from any scheme can be made use of given information on who, when, where and how a record was taken.…”

Section: Understanding and Interpreting Data From Passive Surveillancmentioning

confidence: 99%

The role of passive surveillance and citizen science in plant health

et al. 2020

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The early detection of plant pests and diseases is vital to the success of any eradication or control programme, but the resources for surveillance are often limited. Plant health authorities can however make use of observations from individuals and stakeholder groups who are monitoring for signs of ill health. Volunteered data is most often discussed in relation to citizen science groups, however these groups are only part of a wider network of professional agents, land-users and owners who can all contribute to significantly increase surveillance efforts through “passive surveillance”. These ad-hoc reports represent chance observations by individuals who may not necessarily be looking for signs of pests and diseases when they are discovered. Passive surveillance contributes vital observations in support of national and international surveillance programs, detecting potentially unknown issues in the wider landscape, beyond points of entry and the plant trade. This review sets out to describe various forms of passive surveillance, identify analytical methods that can be applied to these “messy” unstructured data, and indicate how new programs can be established and maintained. Case studies discuss two tree health projects from Great Britain (TreeAlert and Observatree) to illustrate the challenges and successes of existing passive surveillance programmes. When analysing passive surveillance reports it is important to understand the observers’ probability to detect and report each plant health issue, which will vary depending on how distinctive the symptoms are and the experience of the observer. It is also vital to assess how representative the reports are and whether they occur more frequently in certain locations. Methods are increasingly available to predict species distributions from large datasets, but more work is needed to understand how these apply to rare events such as new introductions. One solution for general surveillance is to develop and maintain a network of tree health volunteers, but this requires a large investment in training, feedback and engagement to maintain motivation. There are already many working examples of passive surveillance programmes and the suite of options to interpret the resulting datasets is growing rapidly.

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The potential for citizen science to produce reliable and useful information in ecology

Cited by 131 publications

References 65 publications

The value of long-term citizen science data for monitoring koala populations

The value of long-term citizen science data for monitoring koala populations

Is the Timing, Pace, and Success of the Monarch Migration Associated With Sun Angle?

The role of passive surveillance and citizen science in plant health

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