By N. Kodandapani
Asian Nature Conservation Foundation, Center for Ecological Sciences,
There is uncertainty regarding the extent to which drought, fuel availability, and ignition sources contribute to the global fire regime. In 2004, sharply increased fire activity followed a severe drought, highlighting the importance of droughtÛÒfire linkages in the Western Ghats hotspot of biodiversity. The spatial extent of drought and fire response to the drought was analyzed with 10-year, remotely sensed MODIS NDVI and active fire data, respectively. Estimates of vegetation stress were made in terms of anomalies, as departures from decadal mean, and standardized using standard deviations.åÊ Anomalous fire events were estimated similarly. The average number of hotspots in the Western Ghats over the 10-year period analyzed was 1024å±615. About 23 percent of the total fire occurrences were from 2004, whereas 12 percent were from 2007 and 15 percent from 2009. Eighty-six percent of the hotspots during the 10-year period of analysis occurred during the first quarter, nine percent during the second quarter, one percent during the third åÊquarter, and four percent åÊduring the fourth quarter. During the 2004 drought, the first quarter number of hot pixels (> 1ìÄ) in the Western Ghats increased 47 percent in relation to the 2001ÛÒ2010 mean, while 35 percent of the hot pixels had negative NDVI anomalies. The annual correlation analysis showed a significant positive relationship between first-quarter NDVI and hot pixel anomalies for the wet evergreen primary forest (F1,8=7.06, R2=0.46, p=0.02) and secondary moist deciduous forests (F1,8=14.4, R2=0.64, p=0.005). These anomalous events have important implications for conservation of biodiversity, especially in wet evergreen forests in the Western Ghats.
The consequences of future warm and dry conditions on ecosystem processes such as forest fires have been the focus of several studies on global change (Bowman et al. 2009). In recent years, many studies have reported an increase in the number of wildfires and the area burned in different terrestrial ecosystems across the globe (Westerling et al. 2006; Kodandapani et al. 2004; Dimitrakopoulous et al. 2011). There are uncertainties surrounding the global fire regime, especially the extent to which drought, fuel availability, and ignition sources influence the occurrence of fire.
One of the many consequences of projected global climatic change is an increase in the frequency, intensity, and area affected by extreme drought (Breshears et al. 2005). Since the 1970s, droughts in several tropical regions have been longer and more intense (Malhi and Wright 2004). Increases in tree die-off, flammability (Nepstad et al. 2004), and carbon emissions from fires due to these droughts have the potential to alter regional carbon budgets (Adams et al. 2009).
Although a few studies exist of forest fires in the Western Ghats åÊ(Kodandapani 2013), there is very little information on fires following droughts in the region. In recent years, several remotely sensed vegetation indices have been applied to assess drought through time-series analysis methods (Bhuiyan and Kogan, 2010). In this study, the spatial extent, intensity and impacts of drought were analyzed in terms of anomalies of NDVI. Detailed analysis of a sharply increased fire activity following a severe drought was carried out, highlighting the potential importance of droughtÛÒfire linkages. The objectives of this study in the WG were to estimate the magnitude and pattern of vegetation stress and fire occurrences and to examine the relationship between vegetation stress and fire occurrences in the forest types of the Western Ghats.
The Western Ghats cover an area of 160,000 km2 that stretches for 1,600 km along the west coast of Southern peninsular India, from 21 degrees to 8 degrees north latitude. In the coastal plain, the annual rainfall exceeds 2,000 mm, commonly reaching more than 5,000 mm near the crest of the Ghats. Beyond the crest, a rapid diminishing of annual rainfall to below 1,000ÛÒ1,500 mm is observed within 10ÛÒ50 km of the interior. Correlated with this decrease in rainfall, the length of the dry season rapidly increases in the west-east direction.
The Western Ghats is one of the 34 global hotspots of biodiversity (Mittermeier et al. 2005). Simultaneously, it is the hotspot with the highest human density (Cincotta et al. 2000). The Western Ghats cover only five percent of India’s total land area, but contain more than 4,000, or 27 percent, of the country’s total plant species. Apart from plants, taxonomic groups such as reptiles, mollusks, and amphibians exhibit high levels of endemism. åÊFifty percent of species in these taxa are endemic to the Western Ghats åÊ(Gunawardene et al. 2007). The forests of the Western Ghats are some of the best representatives of non-equatorial, tropical evergreen forests in the world (Pascal 1988).
In this article, only the southern and central parts of the Western Ghats are considered, a study area of 73,784 km2 between 74 and 78 degrees east and 8 to 16 degrees north (Figure 1). Land cover types range from wet evergreen and dry deciduous forest habitatsåÊ to mountain forests and grasslands, alternating with agroforests, monoculture plantations, and agriculture (Renard et al. 2012).
The Tropical Rainfall Measuring Mission (TRMM) satellite provides satellite rainfall estimates as far back as 1998. It uses a passive-sensor microwave imager, active precipitation radar, and visible and IR scanner radiometer (NASA 2006). The microwave imager provides rain rates besides sea surface temperatures[J1]åÊ (SSTs); the active precipitation radar provides estimates of rain parameters.åÊ The rainfall data were obtained from a time series (2001ÛÒ2010) of TRMM data (Tropical Rainfall Measuring Mission, 3B43-v6) at 0.25 by 0.25 degrees (or 774.35 km2) spatial resolution. The cumulative monthly precipitation was estimated in mm month-1 for a 30-day month.
The MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI 16-day composite grid data, C5, MOD13A2, was applied for the vegetation stress analysis. The intensity and duration of the drought across the Western Ghats were calculated in terms of NDVI anomalies, as the departure from the 2001ÛÒ2010 mean (NDVI2001ÛÒ2010) normalized by the standard deviation (ìÄ). NDVI surfaces were grouped into quarters to examine seasonal differences by computing the mean of images that correspond to each quarter. NDVIanomaly was calculated for each year and each quarter on a pixel-by-pixel basis. Thus, NDVI anomaly calculation used quarters for each year and identical reference periods (i.e., 2001 to 2010), for which anomaly was estimated. Since the spatial resolution of the NDVI dataset was one km, it was resampled at 0.25 by 0.25 degrees (or 774.35 km2) spatial resolution to match the hot pixel anomalies.
Hot Pixel Anomalies
The MODIS thermal anomaly dataset, C5, MOD14A1, MYD14A1, was applied for the fire analysis. Fire hotspots are recorded by the MODIS sensors four times in each 24-hour period. The daily MODIS thermal anomaly dataset was downloaded from the MODIS Rapid Response System (available at http://maps.geog.umd.edu/firms/). Compared with other satellite systems, the MODIS hotspot detection system is the most accurate and reliable in terms of detection accuracy and completeness (Roy et al. 2008).
Hot pixel counts were derived from the original MODIS hotspots by aggregating accumulated hot pixels at 0.25-degree spatial resolution. The quarter hot pixel anomalies were then calculated in terms of hot pixel density (accumulated number of monthly hot pixel counts), similar to the NDVI data. To explore the interactions between land cover and climatic conditions on fire patterns, differences in forest type were evaluated. To explore the relationship between NDVI anomalies and hot pixel anomalies, linear regressions were conducted.
Inter-annual Variability of Hotspots in the Western Ghats
The number of hotspots in the Western Ghats showed strong variability across years. The average number of hotspots in the region over the 10-year period analyzed was 1024å±615 (meanå±standard deviation). Three years (2004, 2007, and 2009) during this 10-year period (2001ÛÒ2010) witnessed elevated fire occurrences.åÊ About 23 percent of the total fire occurrences were from 2004, whereas 12 åÊpercent were in 2007 and 15 percent in 2009. Under drought conditions, the total fire occurrences were two-fold higher (2399) in 2004 compared to the 10-year mean. The fire response to the 2004 drought was large within forest types in the Western Ghats. Fire occurrences were approximately two to three times higher in the primary dry deciduous forest and degradation (220å±126) and the primary moist deciduous forest and degradation (166å±142) compared to the 10-year mean. Similarly, in 2004 the fire occurrences were roughly two to three times higher in the wet evergreen primary forest (52å±30) and the secondary moist deciduous forest (123å±93).
Seasonal Pattern of Rainfall and Hotspots for the Western Ghats
The 2001ÛÒ2010 cumulative seasonal rainfall and number of hotspots also showed considerable variations. Figure 2 shows the seasonal variations across the major forest types in the Western Ghats. In the first quarter, the rainfall varied from 13 to 147 mm. Rainfall ranged from 297 to 1115 mm in the second quarter. Much higher rainfall occurred in the third quarter (232-1550 mm). Rainfall declined again in the fourth quarter (135 to 724 mm). Similarly, the cumulative seasonal hotspots also showed variations. Hotspots varied from 203 to 2229 in the first quarter and from 33 to 179 in the second quarter. Much lower fire occurred in the third quarter (3ÛÒ30), but it marginally increased in the fourth quarter (6ÛÒ103). The average number of hotspots during the first quarter (which coincides with the dry season ) in the Western Ghats over the 10-year period of analysis was 880å±596, 94å±50 during the second quarter, 15å±10 during the third quarter, and 35å±30 during the fourth quarter. The year having the highest number of hotspots was 2004, with 2229. 2001 was the year with the lowest number of hotspots (203).åÊ Eighty-six percent of the hotspots during the 10-year period of analysis occurred during the first quarter, nine percent during the second quarter, one percent during the third quarter, and four percent during the fourth quarter.
Hot Pixel Anomalies and NDVI anomalies
During the 2004 drought, the first quarter number of hot pixels (> 1ìÄ) in the Western Ghats increased 47 percent in relation to the 2001ÛÒ2010 mean.åÊ Throughout the first quarter, notable fire anomalies (> 1ìÄ) covered areas from the south to the far north in agreement with the NDVI anomalies of 2004.åÊ Thirty-five percent of the hot pixels had negative NDVI anomalies.åÊ In the year 2007, the first quarter number of hot pixels (> 1ìÄ) in the Western Ghats increased 14 percent in relation to the 2001ÛÒ2010 mean. Ten percent åÊof the hot pixels had negative NDVI anomalies. In 2009, the first quarter number of hot pixels increased 32 percent in relation to the 2001ÛÒ2010 mean. Fourteen percent of the hot pixels had negative NDVI anomalies.åÊ Figure 3 shows the hot pixel anomalies and the NDVI anomalies for the first quarters of 2004, 2007, and 2009.
The seasonal pattern of NDVI and fire anomalies averaged during the period 2001ÛÒ2010 in the Western Ghats are shown in Figure 4. The first-quarter NDVI anomalies and fire anomalies are correlated, but not statistically significant (F1,8=1.9, R2=0.19, p > 0.1), with a coefficient of ÛÒ0.42.åÊ A similar analysis was conducted for the fire season (that is, the first quarter) for individual forest types, as seen in Figure 5. In the wet evergreen primary forest, the first-quarter NDVI anomalies and fire anomalies averaged over the Western Ghats are significantly correlated (F1,8=7.06, R2=0.46, p=0.02), with a coefficient of ÛÒ0.55. In the secondary moist deciduous forest, the first-quarter NDVI anomalies and fire anomalies, averaged over the Western Ghats, are significantly correlated (F1,8=14.4, R2=0.64, p=0.005), with a coefficient of ÛÒ0.55.
Satellite data regarding seasonal NDVI, active fires, and forest types were used to study the climatic effect on burning activity in the Western Ghats. The results supported the idea that the pattern of burning and the inter-annual variability of fires were related to vegetation stress factors. For example, during the years 2004, 2007, and 2009, higher negative NDVI anomalies had a positive effect on fire anomalies in all land cover types, especially in the wet evergreen primary forest and secondary moist deciduous forest. Fires coincided with the dry season. The synergistic effects of future emerging threats to tropical forests, such as warming temperatures (IPCC 2007) and increasing frequency of drought (Williams et al. 2007), along with forest fragmentation (Kodandapani et al. 2004), could cause the wet and moist forests of the Western Ghatsto become åÊfire prone(Bowman et al. 2009).
A combination of drought, human ignition sources, and forest typeåÊ result in elevated fire conditions (Kodandapani et al. 2008). While some forest types in the Western Ghats experienced amplified fire conditions in response to the vegetation stress of 2004, the effects of these wild land fires would vary among forest types, which could be important for conservation in the Western Ghats. In the wet evergreen primary forest, the increased occurrence of fires, especially in drought years, could have important implications for the conservation of biodiversity as demonstrated in similar forests in other parts of the tropics (Cochrane 2003). Tree species in this forest type are not adapted to recurrent fires; drought and fires in this forest type could have impacts on diversity, structure, regeneration, and biomass of these forests (Daniels et al. 1995).åÊ In the secondary moist deciduous forest, local rainfall variations are amplified as a result of large-scale disturbances (Pascal 1988). As a consequence, these two land-cover types could be extremely vulnerable to fires during drought years; together, they constitute about 20 percent of the forest area and harbor high levels of biodiversity. The future consequences of drought, fire, and the resulting mortality of trees (Phillips et al. 2010) could contributing to frequent, destructive fires in these ecosystems.
Although the correlation between fire anomalies and NDVI anomalies for the combined forest types was not statistically significant, it nevertheless demonstrates droughtÛÒfire linkages,åÊ as seen in the NDVI anomalies for the entire Western Ghats. The current study åÊanalyzed a 10-year period. Extending this study over a longer time period would increase sample sizes and provide more robust correlations between these two variables. The Earth observation data such as the MODIS data used in this study are important from a management perspective, as any early warning system regarding fire prevention could be prioritized depending on spatially accurate information on drought and vegetation stress in ecosystems. In combination with in-situ observations of climate and vegetation stress, Earth observations could be used to mitigate the magnitude of destructive fires around the globe.
This study demonstrates the importance of drought intensity and serverity in contributing to anomalous fire events, an important driver of global fire regimes. Increasing intensity, frequency, and area of droughts will have a large impact on fire occurrences in the Western Ghats. Given that several General Circulation Models (GCMs[J1]åÊ) are projecting increasing probability of droughts in the tropics, the long-term effects of recurrent fires in the region could have implications for the conservation of biodiversity in the 21st century. While the spatial and temporal analysis of firesÛª response to drought indicates the vulnerability of all land cover types, the primary wet evergreen and secondary moist deciduous forests are particularly at risk.
The rainfall data used in this study were acquired as part of the TRMM project jointly sponsored by the Japan National Space Development Agency and the U.S. National Aeronautics and Space Administration Office of Earth Sciences. I thank the University of Maryland for kindly providing the fire anomalies dataset. I would like to thank Prof. R. Sukumar for support and Prof. N.V. Joshi for statistical guidance. The assistance of Mr. Beependra Singh with the NDVI analysis is acknowledged.
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