A talk given at TERI University, treating the challenges of detecting and documenting biodiversity change.

1. A. Townsend Peterson
University of Kansas

2. Studying Drivers of Biodiversity Change
• Many potential drivers: land use change, direct
exploitation, climate change, sea level change…
• Anticipate future change: requires present-day
model, and future projections of drivers
• Document change to date: requires detailed
before-and-after views of distributions,
abundances, and/or conservation status
• We will explore both of these approaches…

3. Point-based Distributional Data
• Definition: data records placing a particular
species at a particular location at a particular
point in time
• Primary data – this is the basis of all other
distributional data
• Abundant – millions of specimens, probably
billions of observations are ‘out there’
• Major initiatives – ORNIS, eBird, GBIF, etc.
• Dimensionless – a point has no area; biodiversity
‘points’ have only a basement level of uncertainty
• Useful at any resolution above the basement
level of uncertainty

4. DISTRIBUTED BIODIVERSITY DATABASES
REMIB

5. PROJECTIONS TO FUTURE CLIMATE
CONDITIONS…

6. Ecological Niche Modeling
• Empirical, data-driven
search for associations
between occurrence
and environment
• Significant predictive
ability in hundreds of
studies

12. ADD EFFECTS OF SEA LEVEL CHANGE

13. Sea Level Rise and Coastline Effects

14. US Effects

18. COMPLEMENT vs OVERLAP?

21. MEASURING AVIFAUNAL TURNOVER
IN RECENT HISTORICAL TIMES…

24. Well-sampled Recent Grid Squares

25. Species Gains

26. Species Losses

27. Overall Species Turnover

28. Significant Drivers of Turnover
• Observed precipitation change – NO
significant effect
• Observed temperature change – YES – strong
significant effects
• Human impact on landscapes – NO significant
effect
• BUT – results are coarse in nature …

30. Misantla, Veracruz
Valley of Mexico

34. Methods III
Check coincidence
between the two
sources

35. Quiscalus palustris

43. Sandhill Crane
Grus canadensis
Present-day distribution

44. "Oldmexicocity" by Juan Gómez de Trasmonte, 1628 (d. 17th century) - Mexico Maxico. Licensed under Public Domain via
Commons - https://commons.wikimedia.org/wiki/File:Oldmexicocity.jpg#/media/File:Oldmexicocity.jpg

51. Gran Canal outlet
in Zumpango: «Cajas
del desagüe del gran canal
(1)» de Marrovi - Trabajo
propio. Disponible bajo la
licencia CC BY-SA 3.0 vía
Wikimedia Commons -
https://commons.wikimedia.o
rg/wiki/File:Cajas_del_desag
%C3%BCe_del_gran_canal_(1
).JPG#/media/File:Cajas_del_
desag%C3%BCe_del_gran_ca
nal_(1).JPG

53. Misantla, Veracruz
• 2012 thesis in the
Facultad de Ciencias,
UNAM
• Site well known and
well characterized
from early
ornithological
collections…

55. Misantla 2001-2012

56. Misantla 1850-present
"Battle of Veracruz" by Adolphe Jean-Baptiste Bayot - Originally published in The War Between the United States and
Mexico, Illustrated, 1851. Licensed under Public Domain via Commons -
https://commons.wikimedia.org/wiki/File:Battle_of_Veracruz.jpg#/media/File:Battle_of_Veracruz.jpg

57. Observed Change … Summary

59. Can we do this in India?

62. What’s Missing?

63. BIODIVERSITY INFORMATICS: MAKING
PRIMARY BIODIVERSITY DATA AVAILABLE

64. Biodiversity Informatics Training
Curriculum Courses
• Data Capture
• Biodiversity Inventories
• Data Cleaning
• Data Publishing
• Biodiversity Data Analysis
• Species Descriptions
• Using R
• Using QGIS
• Possibly modules on
Refine, EstimateS (under
development)
• Public Health
Applications
• Ecological Niche
Modeling
• National Biodiversity
Diagnoses
• Conservation
Implementation
• Building Biodiversity
Informatics Institutions

65. Project Webpage

66. Communications - Facebook

67. Interchange – Scientific Journal

68. BITC Version 1.1
• The curriculum is basically complete
– 500+ videos make up the present curriculum
version, covering topics from data capture to
building institutions
• The curriculum is available
– online via the project webpage
– in pdf format via Biodiversity Informatics (soon to
appear)
– on USB keys and in DVD formats (by request)

69. Summary
• Biodiversity is highly dynamic, but the natural
dynamics are augmented by anthropogenic
change in recent decades
• Studying biodiversity change is complex:
– Future projections are hypothetical and hard to test
– Assessments of change already realized are highly
dependent on before-and-after datasets
• Creativity is key in making these studies possible
• Access to abundant and comprehensive data is
crucial to any advances

70. Links
• Town Peterson town@ku.edu
• BITC webpage http://biodiversity-
informatics-training.org/
• Facebook
https://www.facebook.com/groups/Biodi
versityInformatics/