SlideShare a Scribd company logo
Image courtesy of People Productions
Design, sampling
and storage of the
NEON terrestrial
insect collections
Dr. David Hoekman
• Insect Ecologist
• National Ecological
Observatory Network
• dhoekman@neoninc.org
Chironomus islandicus over Mývatn, May 2008 Photo: Árni Einarsson
NEON GoalThe goal of NEON is to enable understanding and forecasting of the
impacts of climate change, land use change and invasive
species on continental-scale ecology by providing data and
infrastructure to support research, education and environmental
management in these areas.
Systematic, standardized sampling across sites
NEON Observing Systems
• Terrestrial observing system (organismal
biology)
• Terrestrial instrument system (climate,
biogeochemistry, soils)
• Aquatic observing system (organismal and
instrumental)
• Airborne observing system (remote sensing)
• STREON (top-down and bottom-up controls,
aquatic)
• Mobile deployable platform
• Land use analysis package (integration with
national data
• NEON collections
The first NEON tower in Sterling, Colorado
A CONTINENTAL-SCALE
OBSERVATION SYSTEM
The National Ecological Observatory will provide access to:
• All data*
• All metadata*
• All QA/QC information (process and data)
• Protocols and procedures used to collect data
• Instrument specifications, characteristics and performance
• Algorithms used to process data
*Unless legally protected by the Endangered Species Act or other legislation
NEON Access Policy
Organismal Sampling
• Plant biodiversity
• Plant biomass, leaf area, and chemical composition
• Plant phenology
• Birds
• Ground beetles
• Mosquitoes
• Small mammals
• Disease
• Soil microorganisms
• Soil biogeochemistry
Terrestrial Observation System (TOS)
TOS – Site Specific Sampling Design
• Spatially balanced design
• Stratified by vegetation
type
• Insects sampled at
biodiversity plots
Terrestrial
Biological
Field
Sampling
Draft site schematic for TOS sampling
Ground beetle sampling
Carabidae
• Charged with measuring
biodiversity and abundance
• Weekly pitfall samples from each
site during the field season
• 4 pitfalls at 10 biodiversity plots for
40 traps per site
• Pinned/pointed
• identified using reference
collection, expert taxonomists,
DNA barcoding
• “by-catch”
Culicidae
• Charged with measuring
biodiversity, abundance and
phenology
• Mosquitoes also being sampled
for disease
• Weekly CDC light-traps (CO2
baited) at the core site, every 4
weeks at relocatable sites at 10
biodiversity plots per site
• Identified using reference
collection, expert taxonomists,
DNA barcoding
• Off-season vs. field season for
phenology
Mosquito sampling
NEON – Generated Natural History Collections
Use existing specimens for DNA barcodes (Construction)
• Validation of field and lab identifications of sentinel taxa
Curation of NEON samples (Operations)
• Voucher collections of sentinel taxa
– For external PI-driven research needs
– Long-term storage
• Range of organisms
• Insects
• Vascular plants and algae
• Animal tissues and genomic extracts
• Microbial communities
• Soils and sediments
DNA barcoding
• Cara’s recent publication
• Integrative Taxonomy for Continental-scale Terrestrial Insect
Observations - PLoS ONE 7(5): 2012
e37528.doi:10.1371/journal.pone.0037528
• Currently contracting with the Canadian Centre for DNA
Barcoding
• all of our records are added to the Barcode of Life
Database (BOLD)
• We will continue to barcode beetles and mosquitoes from
each site/domain as we build up our reference collection
Standing up the observatory
2013
2013
2013
Hoekman ecn 2012

More Related Content

What's hot

International partnerships for ecosystem science_Karan
International partnerships for ecosystem science_KaranInternational partnerships for ecosystem science_Karan
International partnerships for ecosystem science_Karan
TERN Australia
 
New remote and proximal sensing methodologies in high throughput field phenot...
New remote and proximal sensing methodologies in high throughput field phenot...New remote and proximal sensing methodologies in high throughput field phenot...
New remote and proximal sensing methodologies in high throughput field phenot...
CIMMYT
 
High throughput field phenotyping for plant breeding
High throughput field phenotyping for plant breeding High throughput field phenotyping for plant breeding
High throughput field phenotyping for plant breeding
Karthikeyan Periyathambi
 
Next Generation Phenotyping Technologies in Breeding for Abiotic Stress Toler...
Next Generation Phenotyping Technologies in Breeding for Abiotic Stress Toler...Next Generation Phenotyping Technologies in Breeding for Abiotic Stress Toler...
Next Generation Phenotyping Technologies in Breeding for Abiotic Stress Toler...
CIMMYT
 
Will.Stangroom - Resume
Will.Stangroom - ResumeWill.Stangroom - Resume
Will.Stangroom - Resume
William Stangroom
 
USING E-INFRASTRUCTURES FOR BIODIVERSITY CONSERVATION - Module 3
USING E-INFRASTRUCTURES FOR BIODIVERSITY CONSERVATION - Module 3USING E-INFRASTRUCTURES FOR BIODIVERSITY CONSERVATION - Module 3
USING E-INFRASTRUCTURES FOR BIODIVERSITY CONSERVATION - Module 3
Gianpaolo Coro
 
Remote sensing in fruit crops.
 Remote sensing in fruit crops. Remote sensing in fruit crops.
Remote sensing in fruit crops.
KuldeepSingh1530
 
Plant phenotyping systems
Plant phenotyping systemsPlant phenotyping systems
Plant phenotyping systems
Michal Slota
 
Phenotyping in Breeding Programs for biotic stresses
Phenotyping in Breeding Programs for biotic stresses Phenotyping in Breeding Programs for biotic stresses
Phenotyping in Breeding Programs for biotic stresses
International Institute of Tropical Agriculture
 
Metagenomic
MetagenomicMetagenomic
Metagenomic
nasim arshadi
 
Phenomics in crop improvement
Phenomics in crop  improvementPhenomics in crop  improvement
Phenomics in crop improvement
sukruthaa
 
Use of UAV for Hydrological Monitoring
Use of UAV for Hydrological MonitoringUse of UAV for Hydrological Monitoring
Use of UAV for Hydrological Monitoring
Salvatore Manfreda
 
Pollen calendar
Pollen calendar Pollen calendar
Pollen calendar
Alok Kumar
 
Metagenomics: An overview
Metagenomics: An overviewMetagenomics: An overview
Metagenomics: An overview
Jerome Andonissamy
 
UAS based soil moisture monitoring
UAS based soil moisture monitoringUAS based soil moisture monitoring
UAS based soil moisture monitoring
Salvatore Manfreda
 
Metagenomics by microbiology dept. panjab university2018copy
Metagenomics by microbiology dept. panjab university2018copyMetagenomics by microbiology dept. panjab university2018copy
Metagenomics by microbiology dept. panjab university2018copy
deepankarshashni
 
DRONES FOR ENVIRONMENTAL MONITORING
DRONES FOR ENVIRONMENTAL MONITORINGDRONES FOR ENVIRONMENTAL MONITORING
DRONES FOR ENVIRONMENTAL MONITORING
Salvatore Manfreda
 
High-throughput field-based phenotyping in maize
High-throughput field-based phenotyping in maizeHigh-throughput field-based phenotyping in maize
High-throughput field-based phenotyping in maize
CIMMYT
 
Pollen calendar
Pollen calendar Pollen calendar
Pollen calendar
Alok Kumar
 
Lehnert_EGU201_SampleMetadataStandards
Lehnert_EGU201_SampleMetadataStandardsLehnert_EGU201_SampleMetadataStandards
Lehnert_EGU201_SampleMetadataStandards
Kerstin Lehnert
 

What's hot (20)

International partnerships for ecosystem science_Karan
International partnerships for ecosystem science_KaranInternational partnerships for ecosystem science_Karan
International partnerships for ecosystem science_Karan
 
New remote and proximal sensing methodologies in high throughput field phenot...
New remote and proximal sensing methodologies in high throughput field phenot...New remote and proximal sensing methodologies in high throughput field phenot...
New remote and proximal sensing methodologies in high throughput field phenot...
 
High throughput field phenotyping for plant breeding
High throughput field phenotyping for plant breeding High throughput field phenotyping for plant breeding
High throughput field phenotyping for plant breeding
 
Next Generation Phenotyping Technologies in Breeding for Abiotic Stress Toler...
Next Generation Phenotyping Technologies in Breeding for Abiotic Stress Toler...Next Generation Phenotyping Technologies in Breeding for Abiotic Stress Toler...
Next Generation Phenotyping Technologies in Breeding for Abiotic Stress Toler...
 
Will.Stangroom - Resume
Will.Stangroom - ResumeWill.Stangroom - Resume
Will.Stangroom - Resume
 
USING E-INFRASTRUCTURES FOR BIODIVERSITY CONSERVATION - Module 3
USING E-INFRASTRUCTURES FOR BIODIVERSITY CONSERVATION - Module 3USING E-INFRASTRUCTURES FOR BIODIVERSITY CONSERVATION - Module 3
USING E-INFRASTRUCTURES FOR BIODIVERSITY CONSERVATION - Module 3
 
Remote sensing in fruit crops.
 Remote sensing in fruit crops. Remote sensing in fruit crops.
Remote sensing in fruit crops.
 
Plant phenotyping systems
Plant phenotyping systemsPlant phenotyping systems
Plant phenotyping systems
 
Phenotyping in Breeding Programs for biotic stresses
Phenotyping in Breeding Programs for biotic stresses Phenotyping in Breeding Programs for biotic stresses
Phenotyping in Breeding Programs for biotic stresses
 
Metagenomic
MetagenomicMetagenomic
Metagenomic
 
Phenomics in crop improvement
Phenomics in crop  improvementPhenomics in crop  improvement
Phenomics in crop improvement
 
Use of UAV for Hydrological Monitoring
Use of UAV for Hydrological MonitoringUse of UAV for Hydrological Monitoring
Use of UAV for Hydrological Monitoring
 
Pollen calendar
Pollen calendar Pollen calendar
Pollen calendar
 
Metagenomics: An overview
Metagenomics: An overviewMetagenomics: An overview
Metagenomics: An overview
 
UAS based soil moisture monitoring
UAS based soil moisture monitoringUAS based soil moisture monitoring
UAS based soil moisture monitoring
 
Metagenomics by microbiology dept. panjab university2018copy
Metagenomics by microbiology dept. panjab university2018copyMetagenomics by microbiology dept. panjab university2018copy
Metagenomics by microbiology dept. panjab university2018copy
 
DRONES FOR ENVIRONMENTAL MONITORING
DRONES FOR ENVIRONMENTAL MONITORINGDRONES FOR ENVIRONMENTAL MONITORING
DRONES FOR ENVIRONMENTAL MONITORING
 
High-throughput field-based phenotyping in maize
High-throughput field-based phenotyping in maizeHigh-throughput field-based phenotyping in maize
High-throughput field-based phenotyping in maize
 
Pollen calendar
Pollen calendar Pollen calendar
Pollen calendar
 
Lehnert_EGU201_SampleMetadataStandards
Lehnert_EGU201_SampleMetadataStandardsLehnert_EGU201_SampleMetadataStandards
Lehnert_EGU201_SampleMetadataStandards
 

Viewers also liked

The Composite Insect Trap An Innovative Combination Trap for Biologically Div...
The Composite Insect Trap An Innovative Combination Trap for Biologically Div...The Composite Insect Trap An Innovative Combination Trap for Biologically Div...
The Composite Insect Trap An Innovative Combination Trap for Biologically Div...
Myers Shaiyen
 
Me
MeMe
Me
37924
 
Sampling Methods for Surveys
Sampling Methods for SurveysSampling Methods for Surveys
Sampling Methods for Surveys
Plum Voice
 
population dynamics of insects
population dynamics of insects population dynamics of insects
population dynamics of insects
Roberto Kraenkel
 
Population Estimation Methods of Insects by M.Salman
Population Estimation Methods of Insects by M.SalmanPopulation Estimation Methods of Insects by M.Salman
Population Estimation Methods of Insects by M.Salman
Muhammad Salman
 
Population Dynamics
Population DynamicsPopulation Dynamics
Population Dynamics
iamanjie
 

Viewers also liked (6)

The Composite Insect Trap An Innovative Combination Trap for Biologically Div...
The Composite Insect Trap An Innovative Combination Trap for Biologically Div...The Composite Insect Trap An Innovative Combination Trap for Biologically Div...
The Composite Insect Trap An Innovative Combination Trap for Biologically Div...
 
Me
MeMe
Me
 
Sampling Methods for Surveys
Sampling Methods for SurveysSampling Methods for Surveys
Sampling Methods for Surveys
 
population dynamics of insects
population dynamics of insects population dynamics of insects
population dynamics of insects
 
Population Estimation Methods of Insects by M.Salman
Population Estimation Methods of Insects by M.SalmanPopulation Estimation Methods of Insects by M.Salman
Population Estimation Methods of Insects by M.Salman
 
Population Dynamics
Population DynamicsPopulation Dynamics
Population Dynamics
 

Similar to Hoekman ecn 2012

methods of insect sampling in forest
methods of insect sampling in  forestmethods of insect sampling in  forest
methods of insect sampling in forest
Bandana Dandpat
 
Environmental Genomics
Environmental GenomicsEnvironmental Genomics
Environmental Genomics
University of Adelaide
 
Global patterns of insect diiversity, distribution and evolutionary distinctness
Global patterns of insect diiversity, distribution and evolutionary distinctnessGlobal patterns of insect diiversity, distribution and evolutionary distinctness
Global patterns of insect diiversity, distribution and evolutionary distinctness
Alison Specht
 
Bambi presentation
Bambi presentationBambi presentation
Bambi presentation
Klaus Riede
 
Monitoring Project.pptx
Monitoring Project.pptxMonitoring Project.pptx
Monitoring Project.pptx
islamnagi4
 
Ausplots Training - Session 4
Ausplots Training - Session 4Ausplots Training - Session 4
Ausplots Training - Session 4
bensparrowau
 
Session 6: On-farm DNA surveillance
Session 6: On-farm DNA surveillanceSession 6: On-farm DNA surveillance
Session 6: On-farm DNA surveillance
Plant Biosecurity Cooperative Research Centre
 
Abbott utic ecn_2012
Abbott utic ecn_2012Abbott utic ecn_2012
Abbott utic ecn_2012
ECNOfficer
 
Whole genome sequencing of arabidopsis thaliana
Whole genome sequencing of arabidopsis thalianaWhole genome sequencing of arabidopsis thaliana
Whole genome sequencing of arabidopsis thaliana
Bhavya Sree
 
Hyperspectral_Part3_Final.pdf
Hyperspectral_Part3_Final.pdfHyperspectral_Part3_Final.pdf
Hyperspectral_Part3_Final.pdf
TKDMGVHSS
 
Rehab Monitoring - Hyperspectral - Vicki Shaw
Rehab Monitoring - Hyperspectral - Vicki ShawRehab Monitoring - Hyperspectral - Vicki Shaw
Rehab Monitoring - Hyperspectral - Vicki Shaw
Vicki Shaw
 
Developing an Australian phenology monitoring network, Tim Brown, ACEAS Grand...
Developing an Australian phenology monitoring network, Tim Brown, ACEAS Grand...Developing an Australian phenology monitoring network, Tim Brown, ACEAS Grand...
Developing an Australian phenology monitoring network, Tim Brown, ACEAS Grand...
aceas13tern
 
Genetic impacts and climate change Part A, ACEAS Grand, Vicki Thomson
Genetic impacts and climate change Part A, ACEAS Grand, Vicki ThomsonGenetic impacts and climate change Part A, ACEAS Grand, Vicki Thomson
Genetic impacts and climate change Part A, ACEAS Grand, Vicki Thomson
aceas13tern
 
iEvoBio Keynote: Frontiers of discovery with Encyclopedia of Life -- TRAITBANK
iEvoBio Keynote: Frontiers of discovery with Encyclopedia of Life -- TRAITBANK iEvoBio Keynote: Frontiers of discovery with Encyclopedia of Life -- TRAITBANK
iEvoBio Keynote: Frontiers of discovery with Encyclopedia of Life -- TRAITBANK
Cyndy Parr
 
Taylor neon pheno_cam_2014_aceas
Taylor neon pheno_cam_2014_aceasTaylor neon pheno_cam_2014_aceas
Taylor neon pheno_cam_2014_aceas
aceas13tern
 
Perth ausplots presentation_070616_internet_qu
Perth ausplots presentation_070616_internet_quPerth ausplots presentation_070616_internet_qu
Perth ausplots presentation_070616_internet_qu
bensparrowau
 
OBIS at UNGA BBNJ 6th meeting NY 19-23 August 2013
OBIS at UNGA BBNJ 6th meeting NY 19-23 August 2013OBIS at UNGA BBNJ 6th meeting NY 19-23 August 2013
OBIS at UNGA BBNJ 6th meeting NY 19-23 August 2013
UNESCO-IOC/IODE Ocean Biogeographic Information System
 
05 Safety Case Experiences in The Netherlands
05 Safety Case Experiences in The Netherlands05 Safety Case Experiences in The Netherlands
05 Safety Case Experiences in The Netherlands
Sandia National Laboratories: Energy & Climate: Renewables
 
Ruminations on the importance of vouchering, bycatch and accessibility
Ruminations on the importance of vouchering, bycatch and accessibilityRuminations on the importance of vouchering, bycatch and accessibility
Ruminations on the importance of vouchering, bycatch and accessibility
Alex Smith
 
Liddell TERN-super sites-phenology-ACEAS
Liddell TERN-super sites-phenology-ACEASLiddell TERN-super sites-phenology-ACEAS
Liddell TERN-super sites-phenology-ACEAS
aceas13tern
 

Similar to Hoekman ecn 2012 (20)

methods of insect sampling in forest
methods of insect sampling in  forestmethods of insect sampling in  forest
methods of insect sampling in forest
 
Environmental Genomics
Environmental GenomicsEnvironmental Genomics
Environmental Genomics
 
Global patterns of insect diiversity, distribution and evolutionary distinctness
Global patterns of insect diiversity, distribution and evolutionary distinctnessGlobal patterns of insect diiversity, distribution and evolutionary distinctness
Global patterns of insect diiversity, distribution and evolutionary distinctness
 
Bambi presentation
Bambi presentationBambi presentation
Bambi presentation
 
Monitoring Project.pptx
Monitoring Project.pptxMonitoring Project.pptx
Monitoring Project.pptx
 
Ausplots Training - Session 4
Ausplots Training - Session 4Ausplots Training - Session 4
Ausplots Training - Session 4
 
Session 6: On-farm DNA surveillance
Session 6: On-farm DNA surveillanceSession 6: On-farm DNA surveillance
Session 6: On-farm DNA surveillance
 
Abbott utic ecn_2012
Abbott utic ecn_2012Abbott utic ecn_2012
Abbott utic ecn_2012
 
Whole genome sequencing of arabidopsis thaliana
Whole genome sequencing of arabidopsis thalianaWhole genome sequencing of arabidopsis thaliana
Whole genome sequencing of arabidopsis thaliana
 
Hyperspectral_Part3_Final.pdf
Hyperspectral_Part3_Final.pdfHyperspectral_Part3_Final.pdf
Hyperspectral_Part3_Final.pdf
 
Rehab Monitoring - Hyperspectral - Vicki Shaw
Rehab Monitoring - Hyperspectral - Vicki ShawRehab Monitoring - Hyperspectral - Vicki Shaw
Rehab Monitoring - Hyperspectral - Vicki Shaw
 
Developing an Australian phenology monitoring network, Tim Brown, ACEAS Grand...
Developing an Australian phenology monitoring network, Tim Brown, ACEAS Grand...Developing an Australian phenology monitoring network, Tim Brown, ACEAS Grand...
Developing an Australian phenology monitoring network, Tim Brown, ACEAS Grand...
 
Genetic impacts and climate change Part A, ACEAS Grand, Vicki Thomson
Genetic impacts and climate change Part A, ACEAS Grand, Vicki ThomsonGenetic impacts and climate change Part A, ACEAS Grand, Vicki Thomson
Genetic impacts and climate change Part A, ACEAS Grand, Vicki Thomson
 
iEvoBio Keynote: Frontiers of discovery with Encyclopedia of Life -- TRAITBANK
iEvoBio Keynote: Frontiers of discovery with Encyclopedia of Life -- TRAITBANK iEvoBio Keynote: Frontiers of discovery with Encyclopedia of Life -- TRAITBANK
iEvoBio Keynote: Frontiers of discovery with Encyclopedia of Life -- TRAITBANK
 
Taylor neon pheno_cam_2014_aceas
Taylor neon pheno_cam_2014_aceasTaylor neon pheno_cam_2014_aceas
Taylor neon pheno_cam_2014_aceas
 
Perth ausplots presentation_070616_internet_qu
Perth ausplots presentation_070616_internet_quPerth ausplots presentation_070616_internet_qu
Perth ausplots presentation_070616_internet_qu
 
OBIS at UNGA BBNJ 6th meeting NY 19-23 August 2013
OBIS at UNGA BBNJ 6th meeting NY 19-23 August 2013OBIS at UNGA BBNJ 6th meeting NY 19-23 August 2013
OBIS at UNGA BBNJ 6th meeting NY 19-23 August 2013
 
05 Safety Case Experiences in The Netherlands
05 Safety Case Experiences in The Netherlands05 Safety Case Experiences in The Netherlands
05 Safety Case Experiences in The Netherlands
 
Ruminations on the importance of vouchering, bycatch and accessibility
Ruminations on the importance of vouchering, bycatch and accessibilityRuminations on the importance of vouchering, bycatch and accessibility
Ruminations on the importance of vouchering, bycatch and accessibility
 
Liddell TERN-super sites-phenology-ACEAS
Liddell TERN-super sites-phenology-ACEASLiddell TERN-super sites-phenology-ACEAS
Liddell TERN-super sites-phenology-ACEAS
 

More from ECNOfficer

Price2 ecn2013
Price2 ecn2013Price2 ecn2013
Price2 ecn2013
ECNOfficer
 
Sikes ecn2013 dn_ab
Sikes ecn2013 dn_abSikes ecn2013 dn_ab
Sikes ecn2013 dn_ab
ECNOfficer
 
Ryder ecn2013
Ryder ecn2013Ryder ecn2013
Ryder ecn2013
ECNOfficer
 
Janzen ecn2013
Janzen ecn2013Janzen ecn2013
Janzen ecn2013
ECNOfficer
 
Nearns ecn2013
Nearns ecn2013Nearns ecn2013
Nearns ecn2013
ECNOfficer
 
Krell ecn2013
Krell ecn2013Krell ecn2013
Krell ecn2013
ECNOfficer
 
D paul ecn2013
D paul ecn2013D paul ecn2013
D paul ecn2013
ECNOfficer
 
Giddens ecn2013
Giddens ecn2013Giddens ecn2013
Giddens ecn2013
ECNOfficer
 
Rubinoff ecn2013 uhim
Rubinoff ecn2013 uhimRubinoff ecn2013 uhim
Rubinoff ecn2013 uhim
ECNOfficer
 
Mc alister ecn2013
Mc alister ecn2013Mc alister ecn2013
Mc alister ecn2013
ECNOfficer
 
Dombroskie ecn2013
Dombroskie ecn2013Dombroskie ecn2013
Dombroskie ecn2013
ECNOfficer
 
Dmitriev ecn2013
Dmitriev ecn2013Dmitriev ecn2013
Dmitriev ecn2013
ECNOfficer
 
Oboyski ecn2013
Oboyski ecn2013Oboyski ecn2013
Oboyski ecn2013
ECNOfficer
 
Thomas ecn2013
Thomas ecn2013Thomas ecn2013
Thomas ecn2013
ECNOfficer
 
Jones ecn2013 the_goodbadugly conabio
Jones ecn2013 the_goodbadugly conabioJones ecn2013 the_goodbadugly conabio
Jones ecn2013 the_goodbadugly conabio
ECNOfficer
 
Austin ecn2013
Austin ecn2013Austin ecn2013
Austin ecn2013
ECNOfficer
 
Yu ecn2013 cnc_databasing
Yu ecn2013 cnc_databasingYu ecn2013 cnc_databasing
Yu ecn2013 cnc_databasing
ECNOfficer
 
Solis ecn2013 usfws
Solis ecn2013 usfwsSolis ecn2013 usfws
Solis ecn2013 usfws
ECNOfficer
 
Schuh ecn2013 tcn_data_structure
Schuh ecn2013 tcn_data_structureSchuh ecn2013 tcn_data_structure
Schuh ecn2013 tcn_data_structure
ECNOfficer
 
Gil ecn2013 ppt
Gil ecn2013 pptGil ecn2013 ppt
Gil ecn2013 ppt
ECNOfficer
 

More from ECNOfficer (20)

Price2 ecn2013
Price2 ecn2013Price2 ecn2013
Price2 ecn2013
 
Sikes ecn2013 dn_ab
Sikes ecn2013 dn_abSikes ecn2013 dn_ab
Sikes ecn2013 dn_ab
 
Ryder ecn2013
Ryder ecn2013Ryder ecn2013
Ryder ecn2013
 
Janzen ecn2013
Janzen ecn2013Janzen ecn2013
Janzen ecn2013
 
Nearns ecn2013
Nearns ecn2013Nearns ecn2013
Nearns ecn2013
 
Krell ecn2013
Krell ecn2013Krell ecn2013
Krell ecn2013
 
D paul ecn2013
D paul ecn2013D paul ecn2013
D paul ecn2013
 
Giddens ecn2013
Giddens ecn2013Giddens ecn2013
Giddens ecn2013
 
Rubinoff ecn2013 uhim
Rubinoff ecn2013 uhimRubinoff ecn2013 uhim
Rubinoff ecn2013 uhim
 
Mc alister ecn2013
Mc alister ecn2013Mc alister ecn2013
Mc alister ecn2013
 
Dombroskie ecn2013
Dombroskie ecn2013Dombroskie ecn2013
Dombroskie ecn2013
 
Dmitriev ecn2013
Dmitriev ecn2013Dmitriev ecn2013
Dmitriev ecn2013
 
Oboyski ecn2013
Oboyski ecn2013Oboyski ecn2013
Oboyski ecn2013
 
Thomas ecn2013
Thomas ecn2013Thomas ecn2013
Thomas ecn2013
 
Jones ecn2013 the_goodbadugly conabio
Jones ecn2013 the_goodbadugly conabioJones ecn2013 the_goodbadugly conabio
Jones ecn2013 the_goodbadugly conabio
 
Austin ecn2013
Austin ecn2013Austin ecn2013
Austin ecn2013
 
Yu ecn2013 cnc_databasing
Yu ecn2013 cnc_databasingYu ecn2013 cnc_databasing
Yu ecn2013 cnc_databasing
 
Solis ecn2013 usfws
Solis ecn2013 usfwsSolis ecn2013 usfws
Solis ecn2013 usfws
 
Schuh ecn2013 tcn_data_structure
Schuh ecn2013 tcn_data_structureSchuh ecn2013 tcn_data_structure
Schuh ecn2013 tcn_data_structure
 
Gil ecn2013 ppt
Gil ecn2013 pptGil ecn2013 ppt
Gil ecn2013 ppt
 

Recently uploaded

leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
alexjohnson7307
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
panagenda
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
Jason Packer
 
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying AheadDigital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Wask
 
June Patch Tuesday
June Patch TuesdayJune Patch Tuesday
June Patch Tuesday
Ivanti
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
MichaelKnudsen27
 
dbms calicut university B. sc Cs 4th sem.pdf
dbms  calicut university B. sc Cs 4th sem.pdfdbms  calicut university B. sc Cs 4th sem.pdf
dbms calicut university B. sc Cs 4th sem.pdf
Shinana2
 
Trusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process MiningTrusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process Mining
LucaBarbaro3
 
Recommendation System using RAG Architecture
Recommendation System using RAG ArchitectureRecommendation System using RAG Architecture
Recommendation System using RAG Architecture
fredae14
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
Hiroshi SHIBATA
 
Finale of the Year: Apply for Next One!
Finale of the Year: Apply for Next One!Finale of the Year: Apply for Next One!
Finale of the Year: Apply for Next One!
GDSC PJATK
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
Jakub Marek
 
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Malak Abu Hammad
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
Wouter Lemaire
 
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdf
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdfNunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdf
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdf
flufftailshop
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
panagenda
 
Azure API Management to expose backend services securely
Azure API Management to expose backend services securelyAzure API Management to expose backend services securely
Azure API Management to expose backend services securely
Dinusha Kumarasiri
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Pixlogix Infotech
 
Operating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptxOperating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptx
Pravash Chandra Das
 

Recently uploaded (20)

leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
 
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying AheadDigital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
 
June Patch Tuesday
June Patch TuesdayJune Patch Tuesday
June Patch Tuesday
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
 
dbms calicut university B. sc Cs 4th sem.pdf
dbms  calicut university B. sc Cs 4th sem.pdfdbms  calicut university B. sc Cs 4th sem.pdf
dbms calicut university B. sc Cs 4th sem.pdf
 
Trusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process MiningTrusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process Mining
 
Recommendation System using RAG Architecture
Recommendation System using RAG ArchitectureRecommendation System using RAG Architecture
Recommendation System using RAG Architecture
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
 
Finale of the Year: Apply for Next One!
Finale of the Year: Apply for Next One!Finale of the Year: Apply for Next One!
Finale of the Year: Apply for Next One!
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
 
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
 
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdf
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdfNunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdf
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdf
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
 
Azure API Management to expose backend services securely
Azure API Management to expose backend services securelyAzure API Management to expose backend services securely
Azure API Management to expose backend services securely
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
 
Operating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptxOperating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptx
 

Hoekman ecn 2012

  • 1. Image courtesy of People Productions Design, sampling and storage of the NEON terrestrial insect collections Dr. David Hoekman • Insect Ecologist • National Ecological Observatory Network • dhoekman@neoninc.org
  • 2.
  • 3.
  • 4. Chironomus islandicus over Mývatn, May 2008 Photo: Árni Einarsson
  • 5. NEON GoalThe goal of NEON is to enable understanding and forecasting of the impacts of climate change, land use change and invasive species on continental-scale ecology by providing data and infrastructure to support research, education and environmental management in these areas.
  • 7. NEON Observing Systems • Terrestrial observing system (organismal biology) • Terrestrial instrument system (climate, biogeochemistry, soils) • Aquatic observing system (organismal and instrumental) • Airborne observing system (remote sensing) • STREON (top-down and bottom-up controls, aquatic) • Mobile deployable platform • Land use analysis package (integration with national data • NEON collections
  • 8. The first NEON tower in Sterling, Colorado
  • 10. The National Ecological Observatory will provide access to: • All data* • All metadata* • All QA/QC information (process and data) • Protocols and procedures used to collect data • Instrument specifications, characteristics and performance • Algorithms used to process data *Unless legally protected by the Endangered Species Act or other legislation NEON Access Policy
  • 12. • Plant biodiversity • Plant biomass, leaf area, and chemical composition • Plant phenology • Birds • Ground beetles • Mosquitoes • Small mammals • Disease • Soil microorganisms • Soil biogeochemistry Terrestrial Observation System (TOS)
  • 13. TOS – Site Specific Sampling Design • Spatially balanced design • Stratified by vegetation type • Insects sampled at biodiversity plots
  • 15. Ground beetle sampling Carabidae • Charged with measuring biodiversity and abundance • Weekly pitfall samples from each site during the field season • 4 pitfalls at 10 biodiversity plots for 40 traps per site • Pinned/pointed • identified using reference collection, expert taxonomists, DNA barcoding • “by-catch”
  • 16. Culicidae • Charged with measuring biodiversity, abundance and phenology • Mosquitoes also being sampled for disease • Weekly CDC light-traps (CO2 baited) at the core site, every 4 weeks at relocatable sites at 10 biodiversity plots per site • Identified using reference collection, expert taxonomists, DNA barcoding • Off-season vs. field season for phenology Mosquito sampling
  • 17. NEON – Generated Natural History Collections Use existing specimens for DNA barcodes (Construction) • Validation of field and lab identifications of sentinel taxa Curation of NEON samples (Operations) • Voucher collections of sentinel taxa – For external PI-driven research needs – Long-term storage • Range of organisms • Insects • Vascular plants and algae • Animal tissues and genomic extracts • Microbial communities • Soils and sediments
  • 18. DNA barcoding • Cara’s recent publication • Integrative Taxonomy for Continental-scale Terrestrial Insect Observations - PLoS ONE 7(5): 2012 e37528.doi:10.1371/journal.pone.0037528 • Currently contracting with the Canadian Centre for DNA Barcoding • all of our records are added to the Barcode of Life Database (BOLD) • We will continue to barcode beetles and mosquitoes from each site/domain as we build up our reference collection
  • 19. Standing up the observatory 2013 2013 2013

Editor's Notes

  1. Plant biodiversity: inks between biodiversity and ecosystem function Plant biomass, leaf area, and chemical composition: calibration of remotely sensed data -- mapping of plant biomass and the amount of carbon and nutrientsPlant phenology: progression of critical biological processes and ecological eventsBirds: well-known and widely observed indicator of environmental changeBeetles: indicator of significant changes in the local ecological communityMosquitoes: sensitivity to climate variation -- spread of vector-borne diseasesSmall mammals: population dynamics, diversity and diseaseDisease: tick/rodent/mosquito-borne – Lyme, hantavirus, West Nile and dengue Soil microorganisms: spatial and temporal variation community structure/functionSoils: Chemical, physical and biological -- context for plant and microorganism data
  2. Lines of Evidence:Historical ecologicaldataRemote sesning data – spatial variability in biomass; temporal variability in primary productivityActual, on-site data
  3. Based on FIA Plot design================r=7.32 m (24 ft)  .04 acresr=17.95 (58.9 ft)  .25 acresWill likely add microbe and biogeochemistry sampling – co-locate with plant productivity/biodiversity