Transcript Integrated Wetland Bird Management and Monitoring Initiative

Integrated Wetland Bird Management
and Monitoring Initiative
A Structured Decision Making Case Study
So….We in the NWRS Like to Count
Ducks and Other Wildlife.
Why do I
always do
that?
• Its our tradition.
• We like ducks.
• Ducks are
important.
• We manage lots
of places that
ducks like.
• Its fun.
Current Situation
• Wetland management actions are independently
conducted at refuges.
• Little emphasis on sharing data beyond the local
level.
• This independent development of numerous
waterbird monitoring efforts is inefficient and
precludes sharing of data.
• Refuge monitoring efforts lack clear objectives.
Current Situation
• Waterbirds require quality wetland habitats along
their migration route and wintering areas.
• Coordinated efforts to determine if habitat
requirements are being met to support objective
population levels are lacking (Runge et al.
2006).
• Refuges believe that better monitoring will lead
to effective management and contribute toward
larger scale monitoring needs.
• Coordination of management actions and
appropriate monitoring could result in improved
contributions at larger scales.
So What Do We Do?
Implement SHC
Process
• Conducted Internet Questionnaire to
identify waterbird monitoring information
needs across Regions 3,4 and 5.
– 224 Units
– 82 Responses (37% return rate)
– 79% of Respondents indicated that they
monitor waterbirds
Preparation
• Decided to use SDM to address problem.
• SDM workshop scheduled.
• Regional/Flyway Input – 7 questions were
developed to generate input.
• Multiple Conference calls to prepare for
SDM.
– Multi-regional migratory bird program staff
– SDM Participants
– Regional Chiefs and staff talk biology
Problem Statement
We don’t have a monitoring
program to guide decisions at
multiple spatial scales to
sustain migrating and wintering
waterbird populations.
Monitoring Issues
• Lack of linkage between monitoring and
management.
• Lack of linkage between local
management and landscape/flyway
objectives.
• Efficiency.
Resolving These Issues Will
Allow Us To:
• Make all-bird management real.
• Improved science-based
decision-making.
Doing the Right Thing,
in the Right
Place,
at
Efficiently
Connecting
Local for the
the Right
Time,
Management to
Landscape
Goals
Right
Reason
and Objectives
Fundamental Objective
Self sustaining viable populations of
waterbirds in Atlantic and Mississippi
Flyways during migration and winter.
Changing the Monitoring
Paradigm
Adaptive Management Framework for Wetland Birds
Population Model
Population Objectives
(Flyway/Regional)
Habitat Objectives
(Quantity and Quality)
Monitor
1.
Abundance of Birds
2.
Quantity of Habitat
3.
Quality of Habitat
4.
Distribution of Habitat
5.
Cost
Spatial Distribution
(Of Habitat Along Flyway?)
Implement Management Action
(Improve waterbird population
sustainability cost effectively)
Spatial Contribution
(Importance to
population objectives)
(ΔPopulation / Δ Survival)•(Δ Survival/ Δ Manage)•(Δ Manage/ Δ$)
Objectives
Regional / Flyway
Regional /
Flyway
Model
Uncertainty
Regional
Actions
Objectives
Local Mgmt
Uncertainty
Model
Local Mgmt
Local
Actions
Predict
Observe
Objectives and Constraints
• Ensure self-sustaining, viable waterbird populations in
Atlantic and Mississippi Flyway during migration and
winter
• Obj = ∑ ws Ns, t+1 ≥ ∑ wsts
• Minimize habitat quantity and quality deficits
• Budget, data gaps, resistance to change, information
gaps, time, competing objectives and priorities, failure is
not an option.
Influence Diagram
Local Scale Mgmt
Landscape
Config
Other Habitat
Habitat
Acquisition
Regional
Flyway
Input
Convert
Habitat
Wetland
Construction
Objectives
Support and
Dollars
Nt
Habitat Quantity
Patch Size
Energetic
Density
N t+1,i
Available
Habitat
B t +1,in
Timing
Water Depth
Drawdown
Habitat Quality
Mech Treatment
Env
Varialbe
Water Depth
Veg Comp
Herbicide
Inverebrates ?
Human
Disturbance
VOR
% Cover
Human
Disturbance
Veg Structure
Mosq
Control
Available
Habitat
Habitat Quality
(Energy)
Area
Requirement
Land
Cover
Context
Location
Historical
Distribution
Time
Food
Distance
to Coast
Availability
Disturbance
Env.
Var
Influence Diagram
Landscape/Flyway Scale
Mgmt
Cover
Energy Density
Suboptimal
Bad
Good
Suboptimal
Available Habitat
Location Relative
To
Other Sites
Target
Contribution
Value of
Contribution
( Ci )
Acres of
Habitat
Resource
Expentiture
$
Potential
Bird
Use-Days
Habitat
Quality
Habitat
Type
Potential Contribution to Population Sustainability
(Bang for our Buck)
Bird Use (B)
αAH2
∆2
αAH1
Information sent
from field to
Region.
∆1
Funds
AH = Available Habitat
Bi = αAHi + ∆LC * $i * (LC)
Bird Use (B)
aAH2
?2
Decision: Where to allocate
resources so that we maximize
population sustainability.
aAH1
?1
Funds
Sitess
X1
X2
X3
X4
X5
X6
X7
$ ∑Xi = Budget
Obj = ∑ ws Ns, t+1 ≥ ∑ wsts
Responsibility and Timing of Decisions at
Multiple Scales
•
Population Objectives (xx years)
–
•
Authorities shared by Bird Partners. Work thru Joint Venture
Mgmt Boards
Habitat Objectives (xx years)
–
•
Authorities shared by FWS and Land Mgmt Partners
Spatial Distribution (xx years)
–
•
Authorities shared by FWS and Land Mgmt Partners
Allocation of Resources (Annual)
–
•
Regional Scale Land Management Agencies and Partners
Implement Management Actions (Annual)
–
Site Managers
Regional/Flyway Scale
Uncertainty
•
•
•
•
•
•
•
•
Partial Controlability:
Budget
Partial Observability
Estimating parameters within flyway model
Biological Uncertainty
Process to determine site importance.
Environmental Stochasticity
Uncertain if all Partners will
contribute/participate within entire process.
Local Site Uncertainty
•
•
•
•
•
•
Partial Controllability.
Partial Observability.
Estimating parameters within site model.
Biological Uncertainty.
Uncertain about proper mix of abiotic and biotic factors.
Process to determine site contribution (unsure about
shape of curve).
• Environmental Stochasticity (lots)
Recommendations for Future
Development
• Prototype to be evaluated by others, and enhanced.
• Teams to develop decision support models for:
– Energetics, habitat quality and quantity, distribution of
sites, bird abundance.
• Development of monitoring protocols/sample designs.
• Communication with other decision makers in R3, 4, 5.
• Consult additional stakeholders, locally and
ecoregionally
• Consult/communicate with Joint Ventures
• Move beyond jargonality to awsomality
Thanks
• NCTC, Donna and Mike.
• All the Coaches, Consultants,
Apprentices and Observers.
• All Our Team Members.
• Special Thanks to Jim and Eric.
– (We Apologize. We didn’t really
mean to mutiny)
So…. Your done listening to us
for Today
But We’re Just Beginning
I wonder if
there are
any
Questions?
Value of decision structuring
• Linked monitoring to management actions.
• Managing with Partners is critical.
• Allowed us to evaluate management and monitoring in a holistic
manner versus focus on each site independently.
• Value of discussion enhanced by incorporating diversity of
perspectives from team participants who had varying roles within
Wildlife Conservation.
• Transparency that SDM creates. Creating buy-in by others.
Facilitates buy-in.
• Encourages criticism.
•
Evaluating trade-offs. Critical evaluation of alternative actions.
• Implements SHC on the ground.
• Connects refuges using biology into a System, and the contribution
to broader goals.
• Adaptive Mgmt