Assessing the Effects of Land-cover on Native

Transcription

Assessing the Effects of Land-cover on Native
Outline
• Background
Assessing the Effects of Land-cover on
Native Bee Diversity in Eastern North
Dakota
By: Russ Bryant
• Study Sites and Field Methods
• InVEST Habitat Modeling
• Results & Validation
• Implications
Background
• Bees offer a multitude of goods and services
– Ecosystem services
– Commodities
– Medicinal
• Need of pollination services is only increasing
• >95 agricultural plants in the US benefit
– ~$15 billion
• Documented declines in pollinator populations
with some already extinct
• Lack of information on native pollinator species
and their habitat requirements
• Healthy pollinators depend on landscapes that
provide abundant and nutritious sources of noncontaminated pollen and nectar
Causes of Decline
• Destruction and
fragmentation of habitat
•
Poor nutrition
• Parasites and diseases
Objectives
1. Are native wild bees more abundant and diverse where
surrounding land cover contains larger areas of bee-friendly
habitat (herbaceous grasslands, herbaceous wetlands, etc.)?
2. Are floral sources or availability of nesting sites accurate indexes
for measuring native wild bee abundance and richness?
• Pesticides
• Synergistic effect
1
Study Sites in North Dakota
• 8 study sites each roughly 160 acres:
CRP
• 4 USFWS Native Prairie Adaptive
Management (NPAM)
• 4 Conservation Reserve Program (CRP)
• Surveys were done on randomly GIS
generated transects (25m x 2m).
Sully’s Hill
Arrowwood
Kulm
Tewaukon
NPAM
Native Bee Catch
Methods
•
7000
May to September of 2012 and 2013
•
•
8000
Data was collected at each site from:
Blue vane traps were installed at each site per sampling event:
7232
6000
Each vane trap was exposed for 24 hours for each sampling event
•
5662
5659
InVEST Pollination Model and extract predictors
•
Analyze bee abundance and richness with GAMs
Bees Trapped
5000
•
4000
4011
3000
2000
1000
0
2012
2013
CRP
2012
2013
NPAM
InVEST: Integrated Valuation of Ecosystem Services and Tradeoffs
Native bee rank-abundance curve
9000
[CELLRANGE]odes sp.
8000
7000
•
Abundance
6000
5000
InVEST is a family of tools to map and value
the goods and services from nature which are
essential for sustaining and fulfilling human life
•
Agapostemon virescens
Lands and freshwater
•
4000
•
3000
•
Lasioglossum (Dialictus) sp.
Biodiversity, carbon, hydropower, managed
timber, pollination
Oceans and coasts
Wave energy, coastal vulnerability, habitat risk
assessment
Bombus borealis
2000
Lasioglossum (s. str) sp.
Lasioglossum sp.
Bombus ternarius
1000
Halictus confusus
•
Develop varying scenarios for each model
•
Run multiple models with the same data
0
0
20
40
60
Species Rank
80
100
120
2
Pollination Model Data Needs
Ranking land cover
1. Raster land cover
1. Local beekeeper knowledge
2. Table of land cover attributes
•
3. Table of pollinator species
•
1
2. Literature review
Ranking each value as a nesting site and floral resource
3. Personal field experience
Species activity, nesting requirement, flight range
0.5
0
Inputs and Outputs
Satellite Image -> USDA Landcover Data -> Suitable Nesting Habitat -> Floral Sources -> Pollinator Abundance -> Pollinator Service Value
Nesting habitat maps
(ground or cavity)
Pollinator Habitat
(Index of Abundance)
High Quality
Land cover (USDA NASS Cropscape)
Floral source maps
Low Quality
(spring, summer, fall)
High Quality Site
(≥0.5)
Low Quality Site
(≤0.49)
Results
•
No significant variation in annual
bee abundance and sites habitat
index
•
2012 models performed overall
better than 2013 models.
•
Models performed well on
Bumblebees and Melissodes sp.
•
Predicting species richness by floral
sources was highly significant
Floral Resources
Potential Nesting Locations
0
1.25
2.5 Miles
3
Agapostemon sp.
Melissodes sp.
2012
2013
2012
2013
Adj R2
0.19
0.18
Adj R2
0.47
0.17
Deviance Explained
32.2%
31.4%
Deviance Explained
54%
27.7%
AIC
3038.3
2077
AIC
2077.2
2451.2
Lasioglossum sp.
Bombus sp.
2012
2013
2012
2013
Adj R2
0.35
0.33
Adj R2
0.22
0.29
Deviance Explained
42.7%
46.1%
Deviance Explained
43.1%
36.2%
AIC
1602.7
2084
AIC
1672.2
651.2
Richness
Measuring Uncertainty
• 124 bee taxa
2012
2013
Bootstrapping
• Cross-validation using 75% of the data tested against
25%
Minimum
Mean
AICs
1192
1223
Maximum
1245
Residuals
-9.2460
-0.2411
9.6330
Land-cover Rankings
2012
2013
Adj R2
0.33
0.19
Deviance Explained
35.5%
23.9%
AIC
809.8
817.9
• Uncertainty within study sites (35%±18)
• Higher uncertainty nesting availability
• Floral source uncertainty relatively low
4
2013 Estimated Native Bee Habitat
Discussion
•
GAMs oscillations detail:
1.
Resiliency of pollinators in “low-quality” habitat
2.
Uncertainty in rankings of some land-cover classes
3.
Other variables on the landscape influencing native bee
abundance and richness
•
Models suggest areas can be rapidly assessed for floral
sources, therefore potentially healthy pollinator populations
•
Efforts to accurately measure land-cover classes as floral
resources and nesting sites
•
Improved farming practices, increased native floral sources, and
the conservation of high quality habitats can all help maintain
healthy pollinator populations
Acknowledgements:
Literature Cited
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USGS Northern Prairie Wildlife Research Center
USDA Farm Service Agency
US Fish & Wildlife Service biologists and the National Resource Program
Center
CRP private landowners
Field Technicians (Sam O’Dell, Sarah Clark, & Emily Sypolt)
California Cooperative Fish & Wildlife Research Unit
Dr. Jim Graham and Geospatial Modeling
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