Landscapes Forest and Global Change - ESA - Escola Superior ...

A. Altamirano et al. 2010. Human-caused forest fire in Mediterranean ecosystems of Chile
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2. Methodology
The study area extends over 892 km 2 and is located in Eastern Central Chile covering parts of
the Valparaíso and Metropolitan regions (See Figure 2 a). We selected a landscape with
temporal-stability in composition and no other significant processes than fire and succession
operating at the landscape level (Vega-García and Chuvieco 2006).
We used georreferenced forest fires data from a 5-year period of fire occurrence from 2004 to
2008. The database consisted of 7,210 observations, out of which 891 were pixels that burned
between 2004 and 2008. A distance of 25 x 25 pixels (750 m) was used to compute the cooccurrence
matrices, since small windows result in very sparse matrices.
Our data of spatial heterogeneity were obtained at multiple spatial scales, including climatic,
topographic, human-related, and land-cover variables from satellite imagery.
We fit a logistic model in order to predict forest fire occurrence as a function of our potential
predictor variables. The relationship modeled was that between the binary response variable
(one = burned, zero = not burned) and the predictor variables.
3. Result
We selected the best’s no correlated predictor variables. Temperature correlated strongly with
Elevation (r = 0.75) (See Figure 1 a), so only one of the two variables could be used in the same
model. So, we selected Temperature in order to be more biologically meaningful. No significant
correlation was found between Temperature and Precipitation (r = 0.31) (See Figure 1 b). Our
best model suggests that the probability of forest fires occurrence is related to high both
temperature and precipitation, and lower distance to cities (Table 1). The high probability of
forest fire occurrence related to high precipitation could be unusual. However, it can be
explained because the most precipitation is concentrated in the first 500 masl because the local
topographic conditions (See Figure 1 c). Our predictions suggest that 46% (410 km2) of the
study area has high probability of forest fires occurrence, being concentrated in the eastern
locations of the study area (See Figure 2 b). Our model correctly classified about 73% of our
validation dataset.
4. Discussion
The information of this study may be useful for hazard reduction, indicating that risk of forest
fire occurrence (Ryu et al. 2007; Vega-Garcia and Chuvieco 2006). Study area is one of the
most populated regions of Chile. Therefore, our findings can help to take adequate decisions
regarding to land and urban planning.
If climate determines patterns of forest fire occurrence, then when the climatic variables change,
forest fire occurrence should change. This might have important consequences for long-term
land and urban planning, since prioritization of high probability of forest fire occurrence today
might not be effective for the future in the face of climate change.
Exploring new statistical model approach would allow to improving the predictive capability of
the models. So, part of our future research will target to this subject.
References
Calef, M.P., McGuire, A.D., and Chapin, F.S., 2008. Human Influences on Wildfire in Alaska
from 1988 through 2005: An Analysis of the Spatial Patterns of Human Impacts. Earth
Interactions, 12 (1): 1–17.
Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology
Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.)
2010, Instituto Politécnico de Bragança, Bragança, Portugal.