Citizen Science and Big Data: finding the signal amidst the noise

Preview:

DESCRIPTION

Citizen Science and Big Data: finding the signal amidst the noise. Nick Isaac Biological Records Centre, NERC Centre for Ecology & Hydrology @ drnickisaac. Citizen Science. Big Data. Can Citizen Science deliver the data we need to address the environmental challenges of the 21 st century?. - PowerPoint PPT Presentation

Citation preview

Citizen Science and Big Data: finding the signal amidst the noise

Nick IsaacBiological Records Centre, NERC Centre for Ecology & Hydrology@drnickisaac

CitizenScience Big Data

Environmental Challenges

Can Citizen Science deliver the data we need to address the environmental challenges of the 21st century?

Environmental Challenges

FERA

Big Biodiversity Data is here

www.cloudtimes.com

http://www.entangled-bank.org.uk/index.php

www.left.zoo.ox.ac.uk

SUMMARY ECOLOGICAL VALUE

Citizen Science

Citizens

Researchers

Publications

Data collection Feedback, Outreach

Citizen Science is the new black

http://www.ceh.ac.uk/products/publications/understanding-citizen-science.html

Citizen Science Environmental Challenges

paisagemfabricada.com.br

iBats: Citizen Science Big Data

www.ibats.org.uk

The Big Question

• Can Citizen Science deliver the data we need to address the environmental challenges of the 21st century?

The Medium-sized Question

• Can we use existing Citizen Science data to report on the status of biodiversity?

1970 1975 1980 1985 1990 1995 2000 2005 20100

20

40

60

80

100

120

Year

Num

ber o

f site

s

Target 12By 2020 the extinction of known threatened species has been prevented and their conservation status, particularly of those most in decline, has been improved and sustained.

• Population time-series• Annual estimates of status• Taxonomically restricted

How do we know if the targets have been met?

• Red List indices• Many species• Temporally-imprecise

Botham et al (2011) UK Butterfly Monitoring Scheme Annual Report 2011.

Occurrence records: the third way

• 440 million records on

• 90 million records on

• Big Data Citizen Science Environmental Challenges

• Huge potential to detect signals of change

• But the data are noisy!

Problem: ad hoc recording is biased

Problem: ad hoc recording is biased

• in time• in space• detectability• effort per visit

19701975

19801985

19901995

20002005

201010

100

1000

10000

100000

1000000

ButterfliesBryophyteOrthopteraMyriapodIsopodsColeopteraMothsBeesWaspsAntsHoverfliesOdonata

Num

ber o

f rec

ords

Effort

N

umbe

r of S

peci

es

Aggregation into Atlas periods

Selection & Correction methods

Selection• Remove the bias, leave the signal• The ‘well-sampled set’

Correction• by time period, by year, by visit• in space

Occupancy: modelling data collection

Extant Extinct Occupancy (unobserved)

Statistical separation of “state” and “data generation” processes into separate submodels

Observations

Data generation process

Year 1 Year 2 Year 4Year 3 Year 5

Testing the solutions by simulation

• Simple ‘correction’ models fail easily

• Selection methods are robust but less powerful

• Occupancy performs well• in combination with correction and selection

Isaac et al (in press) Methods in Ecology & Evolution

Trends in British Biodiversity 1990-2000• Good news: Median change +2.4%• Bad news: >1000 species would qualify as VU or worse

Identifying drivers of change

Declines in 2-spot ladybird are attributable to the arrival of the invasive Harlequin ladybird

Similar patterns across 8 native species in both GB & Belgium

Roy et al (2012) Diversity & Distributions, 18: 717–725

Mike Majerus

davidkennardphotography.com

The Priority Species Indicator

Source: Biodiversity in Your Pocket 2013

0

20

40

60

80

100

120

1970 1975 1980 1985 1990 1995 2000 2005 2010

Inde

x (1

970

= 10

0)

95% Confidence interval max

95% Confidence interval min

United Kingdom

0

10

20

30

40

50

60

70

80

90

100

Long term

Perc

enta

ge o

f spe

cies

Decline Increase

0

20

40

60

80

100

120

1970 1975 1980 1985 1990 1995 2000 2005 2010

Inde

x (1

970

= 10

0)

95% Confidence interval max

95% Confidence interval min

United Kingdom

0

10

20

30

40

50

60

70

80

90

100

Long term Short term

Perc

enta

ge o

f spe

cies

Decline Increase

Technology-An easy way to record

-Great potential for harvesting meta-data

-Provide instant feedback to the citizen scientist

"The more instantaneously feedback can be provided, the more motivating it is“

www.ebird.org

Phenology Species frequency Species distribution

@NatureNearMe

@NatureNearMe

Looking to the future: more questions

• Which organisms should we prioritize?• Earthworms, Mycorrhizae ….

• How to build and nourish a network of citizen scientists?• Feedback, motivation

• What challenges and opportunities from new data types?• Barcoding, eDNA

• What environmental challenges are on the horizon?• Nanoparticles, Geo-engineering, Biodiversity offsetting

Conclusions

We can report on biodiversity targets for a much wider range of taxa than previously possible

A little bit of meta-data would go a long way

Support the citizens to become more scientific

Addressing big environmental challenges requires fresh thinking

Acknowledgments

Bill Sutherland

Chris Thomas

Tom August

David Roy

Gary Powney

Michael Pocock

Arco van Strien

Recommended