Integrating the Monitoring of Agricultural Pests into Biodiversity Assessments

1. Integrating the Monitoring of Agricultural Pests into Biodiversity Assessments Gail E. Kampmeier Illinois Natural History Survey Institute of Natural Resource Sustainability University of Illinois at Urbana-Champaign

2. Agriculture as a Measure of Biodiversity • Traditionally, • agriculture = downgraded ecosystem • a poor relation to the ideal biodiverse ecosystem of "Nature" • Agriculture has its own challenges • Reduced diversity - easily discovered by pests • Monocultures - species, cultivars • Spatial regularity - row crops, crowding • Selection pressure: environment modified by use of pesticides, resistant cultivars, planting date

3. Wealth of Data • Aside from scientists interested in conservation of genetics of crops & their wild relatives, few agricultural scientists see the value of their data to the biodiversity community • Value in peer-reviewed publications, not data publication • Concern about losing control of their dataset • Biodiversity community has traditionally only paid attention to what is stored in museums or databanks

4. Land Managers, Climate Change Specialists Need • More than one-off collections of taxa • Sampling biased by collector, but not always apparent • Need measures over time of • Presence and absence • Diversity • Under varying conditions

5. Agricultural Research has Rich Data Heritage • Purposefully constructed hypotheses tested in • Variety of (controlled) habitats & (uncontrollable) abiotic conditions • Replicated experimental designs • Examine effects of manipulation of the environment on species behavior • Samples taken at uniform intervals over seasons, years

6. Integrated Pest Management • Sets an economic threshold for making decisions on strategies for maintaining pests at, or below a threshold of economic loss (economic injury level) • The choice of strategies can conserve • Biodiversity • Water, air, & soil quality • money Brewer, et. al. 2009. Opportunities, experiences, and strategies to connect integrated pest management to U.S. Department of Agriculture Conservation programs. American Entomologist 55(3):140-146.

7. Aphids - Pucerons - Afidos • Direct pests of plants • Vectors of plant viruses • Produce honeydew • Food source for ants, predators, & parasitoids • Molds • Damage to crops depends on when & in what numbers they appear in the field Macrosiphum rosae photo courtesy Alex Wild 2008, http://myrmecos.wordpress.com/ Complex life cycle

8. Aphids Move • Walking • Intraplant • Interplant • Flying • Intrafield • Interfield • Migration over 100s of kilometers Cartoon by John Sherrod

9. Tracking the Russian wheat aphid

10. Bugs = "Angel Echoes" CHILL Radar located in Greeley, Colorado

11. Tracking Aphids at Elevations Above Ground Level (AGL) • Air temperature • Insects, including aphids accumulate at or in inversions (temperatures are warmer than the air below) • Wind speed • Below jet, aphids local • In jet, had traveled overnight from sources 240-400 km south from overwintering populations

12. Mapping to Darwin Core • Presence/Absence Observations • Taxon information • Sampling units known volume of air • Large amount of related observations of air temperature, radar observations

13. Soybean Aphid: Invasive Species in North America • Direct pest of soybean • Suction trap network set up in U.S. Midwest • Prediction of infestation level • Indicator to farmers to scout for signs of aphids http://www.ncipmc.org/traps/index.cfm

14. Soybean Aphid Central http://www.inhs.illinois.edu/programs/aphids.html#soybeanaphid

15. Weekly Data • Flights arriving late August built up on late soybean, leaving in September as soybean dried down & flying to Rhamnus

16. Soybean Aphids Swarm Photo courtesy Alex Wild 2009, http://myrmecos.wordpress.com/

17. Weekly Suction Trap Counts in Illinois

18. Simple Darwin Core Most agricultural data fit rows/columns Fields used only once No minimum/ maximum data Will include samples with 0 to multiple observations for a taxon Challenges Human observations (not preserved) thus not given an identifier Asked to think about data in unaccustomed ways Asked to document items usually noted once in a field notebook Implications of Darwin Core for Agricultural Data

19. Example of SimpleDarwinRecord • Easier to use Excel spreadsheet or create a database template to export to Excel

20. Challenges • Mixture of observations & vouchered specimens • Results buried in literature • Little or no metadata for raw data • Scientists have little incentive to go to extra trouble to share

21. Conclusions • If we want to incorporate agricultural datasets into our biodiversity assessments, we will need to work with these scientists to make it easy to provide their data in a format that is fit for use by the biodiversity community. Biocontrol in action!Aphis nerii being eaten by a syrphid fly larva. Photo courtesy Alex Wild

22. How do we do this? • Jim Case provided in talk earlier today, • Bring groups together • Provide introductory guides (documents) • Provide links to resources • Registry system • Discussion forums bring users together • And engage the cooperation of journals to provide a home for data with its metadata

23. Acknowledgments • Illinois Department of Energy and Natural Resources • Illinois Natural History Survey • Illinois State Water Survey • University of Illinois • North Central Regional IPM • National Science Foundation • Hatch ILLU-370 • Global Biodiversity Information Facility • Biodiversity Information Standards (TDWG)