It’s Our Nature to Know Alberta Biodiversity Monitoring Institute Monitoring the cumulative effects of human footprint on biodiversity in Alberta Multi-taxa Monitoring in North America July 18, 2016 – NACCB Madison WI It’s Our Nature to Know Alberta Biodiversity Monitoring Institute Péter Sólymos ([email protected]) with Jim Schieck, Dave Huggard, Ermias T. Azeria, and Marie-Claude Roy
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It’s Our Nature to KnowAlberta Biodiversity Monitoring Institute
Monitoring the cumulative effects
of human footprint on biodiversity
in Alberta
Multi-taxa Monitoring in North AmericaJuly 18, 2016 – NACCB Madison WI
It’s Our Nature to KnowAlberta Biodiversity Monitoring Institute
with Jim Schieck, Dave Huggard, Ermias T. Azeria, and Marie-Claude Roy
The Alberta context
• Population is projected to increase from 4M to 6M by 2040.
• This means increasing demand for resources,
• and challenges for cumulative effects management.
• Public policy expanding as a result (land-use planning, energy, water)
2
Beyond Crises Management
Much of the existing effort focused on crisis management
Broad stewardship and sustainability
information still required
• Proactive
• Broad spatial/temporal scales
• Robust science
• Integrated and cost-effective
3
Pac
ific
So
uth
wes
t R
egio
n U
.S. F
ish
an
d W
ildlif
e Se
rvic
e
• Species at risk
• Habitat at risk (grasslands,
wetlands)
• Acute, localized contamination
What does ABMI do?
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• ABMI was designed to measure cumulative effects of human activity over time.
• Provide the information necessary to manage Alberta’s species and biodiversity (government & industry):– Track changes in habitats & native
vegetation
– Map species abundances
– Determine species habitat associations
– Determine how human land use affects each species
– Assess recovery following reclamation
– Track population changes over time
– Communicate findings to the public
Sampling designrobust to new types of disturbances
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Sites surveyed(2003 – 2014)
Burton et al. 2014 Environ Monit Assess186:3605–3617
Survey protocols
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Sólymos et al. 2013Frontiers in Ecol Env11:178–179
Terrestrial protocolat random location
offset from public location
Aquatic protocolat nearby wetland
Public location
Winter snow transect
Species sampled (>2200)
• Birds,
• mammals,
• vascular plants,
• bryophytes,
• lichens,
• mites,
• aquatic invertebrates.
Chosen based on ease of sampling, statistical properties, and importance to society.
Also sampling: habitat elements, wetland/water characteristics.
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Data and information management
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Sólymos et al. 2015 Wildlife Society Bulletin
39:472–479
Human footprint
Single product integrating all types of human disturbance:• Energy • Forestry• Agriculture• Urban, Rural Residences• Industrial Facilities• Transportation
Where possible built from existing GIS layers.
Some new layers created and validated against satellite images.
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Vegetation
Current vegetationnatural habitats and human footprint• single layer integrating existing info,• broad classes of vegetation
• Species distributions (can the species be there?)
• Habitat and habitat suitability(% of population can be exposed?)
• Extent & type of footprint(is it a hazard?)
• Response to footprint(what is the risk?)
Adaptive monitoring
• Tracks regional changes in habitats, species and biodiversity
• Confront predictions and data, extend and refine models
• Help stakeholders understand ecological changes and associated landscape drivers
13
BiodiversityIntactness
Time
BD
Predictedchange
Observedchange
Recognized in Land-use Planning
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Regional plans must show a long-term vision for the health of biodiversity in the region.
This is done using a regionalBiodiversity Management Framework
2008 – Alberta published the Land-use Framework:• calls for the creation of seven regional plans,• designed to manage the growing pressures on the environment.
Continental scale integration
Design based (standardization)
• Make survey protocol compatible (similar/nested area/time effort)
• Recommendations are usually not followed;best to coordinate efforts.
Model based (reconciliation)
• Find common currency through modeling(probability of occurrence,density)
• Account for differences in protocol / survey effort