Printed on recycled paper U.S. Department of the Interior

U.S. Geological Survey

Fact Sheet 2008–3016

June 2008

Introduction

Central Alaska is ecologically 

sensitive and experiencing stress in 

response to marked regional warming. 

Resource managers would benefit from 

an improved ability to monitor ecosystem 

processes in response to climate change, 

fire, insect damage, and management 

policies and to predict responses to future 

climate scenarios. We have developed 

a method for analyzing ecosystem 

performance as represented by the 

growing season integral of normalized 

difference vegetation index (NDVI), 

which is a measure of greenness that can 

be interpreted in terms of plant growth 

or photosynthetic activity (gross primary 

productivity). The approach illustrates 

the status and trends of ecosystem 

changes and separates the influences of 

climate and local site conditions from the 

influences of disturbances and

land management.

We emphasize the ability to quantify 

ecosystem processes, not simply changes 

in land cover, across the entire period of 

the remote sensing archive (Wylie and 

others, 2008). The method builds upon 

remotely sensed measures of vegetation 

greenness for each growing season. By 

itself, however, a time series of greenness 

often reflects annual climate variations 

in temperature and precipitation. Our 

method seeks to remove the influence 

of climate so that changes in underlying 

ecological conditions are identified 

and quantified. We define an “expected 

ecosystem performance” to represent 

the greenness response expected in a 

particular year given the climate of 

that year. We distinguish “performance 

anomalies” as cases where the ecosystem 

response is significantly different from 

the expected ecosystem performance. 

Maps of the performance anomalies 

(fig. 1) and trends in the anomalies give 

valuable information on the ecosystems 

climatic conditions differently from that 

of most other areas.

Results

Ecosystem performance anomaly 

maps were produced for each year 

from 1996 to 2004. The map in figure 1 

shows the 2004 season. The maps were 

colored to reflect negative anomalies 

(underperforming), positive anomalies 

(overperforming), and normal pixels 

as determined in figure 2. Numerous 

underperforming anomalies were 

associated with burn severity in areas 

with confirmed forest fires. Other 

explanations for underperformance 

were insect infestations and a drier soil 

associated with a thickening soil active 

layer. Overperforming areas were mostly 

areas of expanding deciduous forest. The 

northern limits and higher elevations of 

the boreal forest are also experiencing 

more favorable growing conditions 

because of climate change.

for land managers and policy makers at a 

resolution of 1 km to 250 m.

Methods

A model is developed from random 

pixels representing a range of yearly 

climatic conditions and numerous 

site conditions to predict growing 

season NDVI (expected ecosystem 

performance). Yearly maps of expected 

growing season NDVI are constructed 

from this model with the use of 

spatial climatic data and site potential 

values. Site potential is the historical 

performance related to elevation, slope, 

aspect, soils, and other factors. Dry 

years have lower expected ecosystem 

performance and wet years have higher 

expected ecosystem performance. Areas 

that do not perform within the normal 

range determined by the regression tree 

model’s expected error are identified as 

ecosystem performance anomalies. These 

anomalies are areas that are responding to 

Figure 1. Ecosystem performance anomaly for 2004, with perimeters of fires that occurred 

between 1997 and 2004. The colored portion of the image represents the boreal forest areas 

of Alaska within the Yukon River Basin.

253

-283

113

-112

Perimeters

of fires that

occurred 

between 1997 

and 2004

Boundary of 

Yukon River

Basin

Underperformance Overperformance

units of Normalized Difference Vegetation Index (NDVI)

Land Remote Sensing, Geographic Analysis and Monitoring, and Earth Surface Dynamics Programs

Modeling and Dynamic Monitoring of Ecosystem

Performance in the Yukon River Basin
temporally detailed record of anomalous 

performances, trends, and abrupt 

changes. This project will be completed 

as a contribution to the International 

Polar Year.

By B.K. Wylie1, L. Zhang2, L. Ji1, 

L.L. Tieszen3, and N.B. Bliss1

1 ASRC Research and Technology Solutions, 

contractor to the U.S. Geological Survey Earth 

Resources Observation and Science (EROS) Center. 

Work performed under contract 08HQCN0007.

2 Science Applications International Corporation, 

contractor to the U.S. Geological Survey Earth 

Resources Observation and Science (EROS) Center. 

Work performed under contract 03CRCN0001.

3 U.S. Geological Survey.

References

Wylie, B.K., Zhang, L., Bliss, N., Ji, L., Tieszen, 

L.L., and Jolly, M., 2008, Integrating modeling 

and remote sensing to identify ecosystem performance anomalies in the boreal forest, Yukon 

River Basin, Alaska: International Journal of 

Digital Earth, v. 2, p. 196–220.

areas associated with an increasing 

deciduous forest component could 

provide vegetation-change models with 

spatial source locations to predict the 

future extent of deciduous forests.

The current (2008) availability 

of Moderate Resolution Imaging 

Spectroradiometer (MODIS) data (250-m 

resolution) promises higher resolution 

for future applications in both the 

United States and Canadian parts of the 

Yukon River Basin. Archived Advanced 

Very High Resolution Radiometer 

(AVHRR) data at a 1-km resolution for 

the period 1985–present will allow us to 

produce a complete, spatially rich and 

Figure 3 shows how the ecosystem 

performance anomaly became more 

negative or positive from 1996 to 2004. 

Ninety percent of the area did not show a 

significant trend (p ≥ 0.20) in ecosystem 

performance anomaly. There were more 

areas with negative trends than positive 

trends. Negative trends were commonly 

associated with areas where fires had 

occurred after 1998. Positive trends 

were commonly associated with areas 

that had burned prior to 1995 and may 

represent deciduous postfire species and 

ultimately coniferous forest recovery. 

There are numerous examples, however, 

of both positive and negative trend areas 

not associated with fires. The negative 

trends may represent areas of insects, 

disease, or changing permafrost and 

active layer thickness. The positive trends 

may indicate increasing deciduous forest 

composition.

Using Ecosystem Performance

Identification of localized areas 

of disturbance or “climate change hot 

spots” is essential for regional modeling 

of carbon fluxes and future dominant 

vegetation complexes. Including localized 

and fragmented non-fire disturbances at 

a regional scale would improve regional 

carbon flux estimates. Underperforming 

areas are areas that may benefit from 

interventions to enhance boreal forest 

health or recovery. Some of these 

underperforming areas may be associated 

with degrading permafrost—a process 

that can be verified through additional 

field data collection. Overperforming 

Figure 2. Model predictions 

of expected ecosystem 

performance compared 

with actual ecosystem 

performance for multiple 

years. Pixels were selected 

randomly from boreal 

forest areas that have not 

burned in 25 years. Green 

and yellow areas represent 

overperformance and are 

greater than the 90-percent 

confidence limit above the 

regression line. Magenta 

and red areas represent 

underperformance and are 

less than the 90-percent 

confidence limit below the 

regression line.

Figure 3. Ecosystem performance anomaly trends for the boreal forest region in the Yukon 

River Basin, Alaska, 1996–2004. The image is stratified according to the direction (positive or 

negative) and significance (t-test probability, p) of the slope of the regression line through

the ecosystem performance anomaly values for each pixel.

Expected Ecosystem Performance, in units of

Normalized Difference Vegetation Index (NDVI)

Ecosystem Performance, in units of

Normalized Difference Vegetation Index (NDVI)

400

400

1600

1400

1200

1000

800

600

600 800 1000 1200 1400 1600

R2 = 0.84

Standard error 

= 67.0 Disturbance

Climate

Overperformance

Normal

Underperformance

at p < 0.05

at p < 0.10

at p < 0.20

not signif. p> p 0.20

at p < 0.20

at p < 0.10

at p < 0.05

High

Low

Elevation

Trend

Positive

Negative

For more information, contact:

Larry L. Tieszen, Project Manager

U.S. Geological Survey

Earth Resources Observation and 

Science (EROS) Center

47914 252nd Street 

Sioux Falls, SD 57198–0001

Phone: 605–594–6056

Email: tieszen@usgs.gov