Transcript Complexity Across Boundaries: Coupled Human

Complexity Across Boundaries: Coupled Human and Natural Systems in
the Yellowstone Northern Elk Winter Range (NEWR)
Cast of Characters
Dr. David McGinnis (ISU, PI)
Dr. Jason Shogren (UW, Co-PI)
Dr. David Bennett (UI, Co-PI)
Dr. William Travis (UC, Co-PI)
Dr. Duncan Patten (MSU, Co-PI) Dr. Bob Crabtree (YERC)
Dr. Mark Lewis (UA)
Dr. Marc Armstrong (UI)
Dr. Richard Horwitz (UI)
Specific objectives for this project:
1. Assess the knowledge/belief systems of NEWR stakeholders with respect to environmental
change and ecosystem service and relate these systems to socio-economic characteristics
and stakeholder identity.
2. Improve and expand the empirical record associated with land-use/cover change and use
this record to model the impact of development and other human activities on the NEWR.
3. Improve and extend individual-based models that represent large-mammal behavior.
4. Develop plausible climate scenarios that illustrate how the NEWR may adapt to global
climate change/variability.
5. Use knowledge gleaned from 1 through 4 to model decision-making using quantitative
(intelligent agents) and qualitative (scenario analyses) methods and to merge the
biophysical and decision-making models into an ecosystem model that allows us to explore
alternative future scenarios for the NEWR.
HUMAN SYSTEM MODEL
Dr. Jerry Johnson (MSU)
Dr. Bruce Maxwell (MSU)
Dr. Sheila McGinnis (ISU)
Dr. Charles Peterson (ISU) Mr.. Wenwu Tang (UI)
Dr. Paul Robins (OSU)
Ms. Lifang Huang (UI)
Dr. Mark Williams (UC-B)
Ms. Julia Haggerty (UC-B)
Mr.. Craig Anderson (UC-B)
Dr. Mark Lung (ISU)
Dr. Eric Noonberg (YERC)
Elk-Human interaction? (http://www.nps.gov/yell/safetyvideos.htm)
Northern Elk Winter Range (www.nps.gov/yell/nature/northern range/natreg/ map.html)
Rose Creek wolf pack near elk trail. (http://www.nps.gov/yell/press/images/wildlife/wolf pack.jpg)
CONCEPTUAL DIAGRAM
PHYSICAL SYSTEM MODEL
Snow
Exogenous Shifts
# and location
hunters
# and location
licenses
Policy affects land
managers
Regulation
Change
Fish & Game
Formula
Policy makers
Climate
Vegetation
Disease
Perception
a
Precip
Wolf
Temp.
Prey
Snow
Rainfall
Stream
Beaver
Land
Managers
Land Value
Conversion
of LC
Change in LU
Human subsystems affect
the biophysical sub-systems
Ownership/
Mgmt change
LANDSCAPE
Biophysical subsystems
affect the human subsystems
Groundwater
Soil Water
Biological
Population
Events
Elk
Aspen
a
State changes in
biophyscial
systems
a
Willow
Grass/shrub
Elk
Amphibian
Disease (CWD)
Wolf
Biophysical system
Hunter
Demographics
Predators
State changes within human
sub-systems
a
Hunter
behavior
Land managers affect policy
# of
permits
Regulation
change
Perception of
over-population
Livestock
Mortality
Predator Tol.
Scenarios
A Postulate:
Physical
 Wolf predation affects the spatial pattern of elk, concentrating them into areas of
low predation pressure
Arial photos indicating 100 meter radius zones of
influence around house site points (left) and 100
m radius house site zones of influence colored to
show intersection with different land use/cover
types. To assess how humans make decision
regarding land use, qualitative interviews are
being conducted. Results from these interviews
will help explain why change happens and will
provide input to the land-use change models.
 Within these areas willow and aspen become over browsed which in turn has a
negative impact on riparian habitat.
$
 The wolf population responds to the new spatial pattern of elk (different packs
prosper) and a new spatial pattern of predation evolves.
$
 In response, elk adapt, reducing the pressure on plant resources in one area and
increasing it in another.
$
$
$
$
$
 Thus creating a shifting pattern of resource use that is sustainable at the landscape
level.
$
Land use transition diagram for generalized land
use/cover types in the Upper Yellowstone Valley Disturbed
for the period between 1948 and 1998. Historical
land use data provides a robust way to analyze
89%
1%
environmental change. These changes will be
related to demographic change and human Grassland
decision-making systems and will be used to
project future ecosystem change resulting from
human activities.
79%
0.5%
13%
Agriculture
7%
1%
1%
2%
 Perhaps humans have modified this pattern.
5%
11%
1%
87%
Riparian
Shrub land 18% Forest
82%
By removing two key elements of the ecosystem, wolves and beaver, and by
restricting elk movement to the upper part of their traditional migration range
through development and hunting, humans may have artificially constrained this
spatio-temporal cycle.
As a result, willow and aspen do not recover from elk browsing and, as a result,
riparian habitats that support beaver and amphibian populations suffer. The
system has, perhaps, entered into a new state with reduced stability.
 Confounding factors include climate change, changes in predator-prey
relationships, changes in economics and demographics, etc.
Human System Changes:
Development
Ranching
Hunting regulation
Wildlife management strategies
Climate classification system using
non-linear Kohonen Self-Organizing
Maps (SOMs) on 700 hPa geopotential
heights. Each day is classified into a
single map node shown at right. Daily
snowfall water equivalence can be
modeled for each SOM node to
provide input to a snow model (depth,
density, and character) that will then
be used as input to an elk energetics
model (snow depth and characteristics
are crucial for winter feeding habits,
migration, and predator avoidance).
The elk model will be incorporated
into an agent-based, spatially explicit
GIS model to demonstrate how
changing conditions modify elk
behavior and vice versa. The annual
snow accumulation will also be used
in the groundwater-riparian habitat
modeling.
(NSF Biocomplexity in the Environment (BE) – Dynamics of Coupled Natural and Human Systems (CNH) Award #0216588)
Not modeled