Extracting time series from occurrence records Nick Isaac Cross-taxa analysis of community dynamics: 4/11/15

Environmental Monitoring in the UK Intensity Volume Sentinel sites National surveys National Monitoring Schemes Unstructured occurrence records

= terrestrial ECN sites = ECN river sites = ECN lake sites Environmental Change Network Sentinel sites Multi-metric integrated monitoring: Meteorology Atmospheric deposition Bulk soil analysis Soil chemistry Runoff chemistry Vegetation quadrats Butterfly, bird & bat transects Moth light traps Beetle pitfall traps Morecroft et al (2009) Biol Conserv

Countryside Survey National professional surveys in 1978, 1984, 1990, 2000, 2007 Stratified random sampling with 1km 2 grain size Vegetation plots Landscape features National Sample based Freshwater macrophytes Soils Norton et al. (2012) J Env Manag 113:

National Monitoring Schemes Birds: BBS, WeBS, WBS, WBBS …. Butterflies: UKBMS, WCBS Moths: RIS Bats: NMRS Some terrestrial mammals Plants: NPMS Volunteers collect, professionals curate Partnerships with NGOs are crucial

UK Butterfly Monitoring Scheme WCBS Pollard walks

Severe droughts impacts on butterflies Managing landscapes (e.g. reducing habitat fragmentation), the probability of persistence until mid-century improves from around zero to between 6 and 42% Figure: a.Low fragmentation level b. & c. Mid d.High fragmentation level e.Current situation Oliver et al. (2015). Nature Climate Change doi: /nclimate2746

Unstructured Occurrence Records

Shift between Key Publications: Hickling et al Global Change Biology; Chen et al Science

What are national schemes and societies?

Time series from occurrence records Recording is biased Occupancy models as a solution Applications Broad patterns in biodiversity Resilience of ecosystem services Trends among British bees Biodiversity Indicators Drivers of biodiversity change

Problem: ad hoc recording is biased in time in space detectability effort per visit Effort Number of Species Isaac & Pocock (2015) Biol J Linn Soc 115:

Occupancy models: a solution? WildAboutBritain.co.uk van Strien et al (2011) Ecol Appl 21: 2510–2520 Bayesian Occupancy-Detection (BOD) models van Strien and others have argued that BOD provides a framework for modelling unstructured occurrence records van Strien et al (2010) Basic & Appl. Ecol. 11: van Strien et al (2011) Ecol. Appl. 21: van Strien et al (2103) Biodiversity & Conserv 22: van Strien et al (2013) J. Appl. Ecol. 50: Observer model: (p D |z) ~ ListLength

Occupancy models are robust to biases BOD models are robust to several forms of biases in opportunistic data, and more powerful than other methods Isaac et al (2014) Methods in Ecology & Evolution 5:

Defaunation Review Dirzo et al (2014) Science, 345: 401–406

Species trends and ecosystem functions Turnover is higher among species that deliver pollination and pest control services These functions may be less resilient to change Oliver et al (in review)

Occupancy models for British bees Nick Owens Bombus bohemicus

Indicator of Pollinating Insects from Occupancy models for 216 bee species

Drivers of change: Invasive ladybird Declines in native ladybirds 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

Declines in native ladybirds

Where next? The ideal dataset for studying global change has broad taxonomic and spatial coverage with fine spatio-temporal resolution No dataset has all these properties Beck et al (2012) Ecography 35: 1-11

Existing datasets are complementary What is the best way to model biodiversity responses to environmental change? TraitEnv Change Network Countryside Survey Monitoring schemes Occurrence Records ProtocolsDetailed SimpleNo Stratified designNoYesmixedNo Co-locationYesNolimitedNo Taxonomic breadthlimited high Temporal precisionhighlowMostly goodhigh Spatial coveragelowhighmixed Spatial extentNational International

Model datasets together It’s not an either-or question Each is a separate realization of the same underlying state Borrow strength across datasets

Conclusions UK has a wealth and diversity of biodiversity data Some are scalable across Europe Opportunistic records can provide valuable insights – climate change – ecosystem services – Invasive species Best value from combining datasets – New hybrid schemes are under development

Acknowledgments Tom August, Gary Powney, David Roy, Charlie Outhwaite Arco van Strien, Marnix de Zeeuw Colin Harrower, Helen Roy, Michael Pocock, Oli Pescott, Stephen Freeman Mark Hill, Chris