Although the vast majority of contemporary wildfires in the Upper Midwest o
f the United States have a human origin, there has been no comprehensive an
alysis of the roles played by abiotic, biotic, and human factors in determi
ning the spatial patterns of their origins across the region. The Upper Mid
west, a 2.8 x 10(5) km(2) area in the northern, largely forested parts of t
he states of Minnesota, Wisconsin, and Michigan, contains regions of varied
land cover, soil type, human settlement densities, and land management str
ategies that may influence differences in the observed spatial distribution
of wildfires. Using a wide array of satellite- and ground-based data for t
his region, we investigated the relationship between wildfire activity and
environmental and social factors for >18 000 reported fires of ail sizes be
tween 1985 and 1995. We worked at two spatial scales to address the followi
ng questions: (1) Which abiotic, biotic, and human variables best explained
decade-scale regional fire activity during the study period? (2) Did the s
et of factors related to large fires differ from the set influencing all fi
res? (3) Did varying the spatial scale of analysis dramatically change the
influence of predictive variables? (4) Did the set of factors influencing t
he number of fires in an area differ from the set of factors influencing th
e probability of the occurrence of even a single fire?
These data suggest that there is no simple "Lake States fire regime" for th
e Upper Midwest. Instead, interpretation of modern fire patterns depends on
both the fire size considered and the measurement of fire activity. Spatia
l distributions of wildfires using two size thresholds and viewed at two sp
atial scales are clearly related to a combination of abiotic, biotic, and h
uman factors: no single factor or factor type dominates. However, the signi
ficant factors for each question were readily interpretable and consistent
with other analyses of natural and human influences on fire patterns in the
region. Factors seen as significant at one scale were frequently also sign
ificant at the other, indicating the robustness of the analysis across the
two spatial resolutions. The methods for conducting this spatially explicit
analysis of modern fire patterns (generalized linear regression at multipl
e scales using long-term wildfire data and a suite of environmental and soc
ial variables) should be widely applicable to other areas. Results of this
study can serve as the basis for daily, seasonal, or interannual studies as
well as the foundation for simulation models of future wildfire distributi
on.