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Article
Study of fire and land change, land use within the Bay of Jiquilisco region of
El Salvador
M. Nichols1
and J. Miller1
1
Department of Geography & Environmental Studies, University of Colorado, Colorado Springs,
CO 80918, USA; mnichols@uccs.edu and jmiller@uccs.edu
Introduction
Critical habitats provide important ecological services in the form of biodiversity in flora
and fauna, elemental regulation, and inter-ecosystem bio-corridors. These habitats provide
anthropogenic services, such as material extraction, aquaculture, and sustenance farming to
surrounding communities and outlying population areas. These services are used for local
livelihoods and to increase local economies. Critical habitats include wetland ecosystems that
include fresh and brackish marshes, seagrass beds, and mangroves forests.
Mangrove forests exist in over 80 countries on five continents with an estimated global
area of between 110,000 and 240,000 km2
(Giri et al. 2011). Mangroves are complex,
multilayered coastal environments that provide vital ecosystem services. These ecosystem
services include: coastal interface regulations, species habitat, waste treatment, biomass
production, carbon sequestration, and inter-ecosystem nutrition transfer and capture. Mangrove
systems also provide anthropogenic services in the form of firewood, building material, fishery
and shrimp pond aquaculture, sustenance farming, medicinal plant extraction, and flood
protection. These ecosystem services provide a value of $1.6 billion USD/yr. at the global level
(Polidoro et al. 2010).
Between 1980 and 2000, a 35% decrease occurred in global mangrove land cover (Giri et
al. 2011). Based on the multitude of different management techniques and policy enforcement of
various countries, a 1%-20% loss of mangrove forest area per year occurred. Mangrove forests
face threats from multiple sources, both natural and anthropogenic. Ecological threats include sea
level rise (SLR), increased storm events, the decline of partner ecosystem health, and climate
change. Anthropogenic threats include deforestation due to urban development, agriculture and
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aquaculture expansion, increased population, tourism, overexploitation of resources,
hydrological diversion, pollution, and fire. Approximately 30% of regional populations inhabit
areas directly exposed to adverse storm events, high tides, tsunamis, and flooding (Lacambra et
al. 2011). These are all events that mangrove forests adapt to and regulate, which assists in the
prevention of coastal erosion and property loss( ).
Fire has been one of the most comprehensive tools for forest clearing and repurposing in
the tropical regions (Chuvieco et al. 2008). This makes fire the most commonly used tool for
land cover change. Fire has also been extensively used in support of active landscape
management, particularly with regards to clearing for agricultural purposes (Bowman et al.
2009). With respect to the reduction and elimination of agricultural waste, fire has been
implemented and employed in the removal of vegetation species as well as promoting desired
vegetation species (Yevich et al. 2003). Anthropogenic burning is one of the primary threats to
mangrove forest systems. Within the Central American region, fire patterns indicate that it is
widely used, with many detected fire events occurring along the coastal corridors (Figure 1).
Fire continues to redefine Central America’s land cover and land use (LCLU). Due to fire
effects, it remains imperative that the monitoring of LCLU occur with the use of remote sensing
and GIS techniques which can capture the spatial extent of LCLU change and intensity of fires
and burned areas.
LCLU can impact a critical habitat either positively or negatively. For example, the
measurement of LCLU can help assist defining the gains and losses of a particular ecosystem
land cover classification. These measurements can help in determining what constitutes a threat
to critical habitats in relation to biodiversity loss, water inundation, and anthropogenic resources.
Study Area
The Bahía de Jiquilísco Reserve and the subset Monte Cristo mangrove are located on the
central coast of El Salvador, east of the Rio Lempa (Figure 2). The area constitutes the largest
extension of brackish water and salt water forest in El Salvador. This reserve contains numerous
estuaries, canals, sand dunes, beaches, isles, freshwater lagoon, and seasonally saturated forests
connected to the mangroves. The Reserve is habitat and nesting site for numerous coasting bird
species, such as the frigate, osprey, pelican, and crane. The reserve also constitutes a critical
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nesting site for a half dozen endangered sea turtle species, such as the Hawksbill, olive ridley,
and leatherback.
Bordered by the settlements of Monte Cristo, La Canoa, San Juan del Gozo, and Isla de
Mendez, the mangrove forest is surrounded by cultivated agricultural areas. The land
management dynamic within the reserve included communal management, private land, and
state-owned. Due to heavy deforestation in the past there is limited remaining forest land cover.
This creates a landscape where agricultural fields and plots occupy the same space as forest
stands. Economic activities involve fishing, shellfish extraction, agriculture, salt extraction, cattle
ranching, coconut plantations, with some area seeing increased tourism. This research examines
the distribution of this mangrove system and surrounding land cover. MODIS fire data is
incorporated to determine fire patterns that may correlate with land cover change within this
region of El Salvador.
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Methods
Landsat 7 ETM +
satellite imagery was acquired from USGS – Earth Explorer and
consisted of 11 separate images, date ranging from December 2003 to 30 December 2013. All
satellite images contained minimal to no cloud cover and satellite imagery was selected in
accordance with a previous study entitled, “Interactions between Climate, Land Use and
Vegetation Fire Occurrences in El Salvador,” which found that December through February are
the driest times during the year with the most detection of fires (Armenteras et al. 2016).
Therefore, images in the December time-frame between the years 2003 to 2013 annually were
used. The study area comprises an area of roughly______sq. miles.
Landscape percentages for the Bay of Jiquilisco Reserve region were derived from using
IDRISI-SELVA software’s Unsupervised Land Classification which uses an algorithm to
differentiate between spectral classes and informational classes. The Unsupervised Classification
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method was incorporated into the research because of a lack of first-hand knowledge of the area
such as terrain features and/or any other identifiable features whereas information classes could
be assigned. Informational classes included water, closed forest, open vegetation, agriculture,
bare soil, and built. After informational classes were identified, groups of pixels were placed into
spectral classes using an Isoclust. Next, using the Symbol Workshop, informational groups were
assigned to a spectral group on a best matching basis and each spectral group was reassigned to
an informational class. To obtain landscape percentages for each time span, the Unsupervised
Classification Isoclust’s histogram for each perspective time period was opened and the
cumulative frequency no data pixels were subtracted from the total number of no data pixels in
the Unsupervised Classification Isoclust. That difference was divided into each informational
classes' cumulative frequency of pixels which resulted in the percentage of landscape.
The data utilized to develop this study included Moderate Resolution Imaging
Spectroradiometer (MODIS) fire data from 2001-2015 and land use/land cover data from 2001-
2012 covering Central America. This data was reduced to study just the country of El Salvador.
Landsat 7 ETM+ SLC-off images from 2004, 2008, and Landsat 8 OLI/TIRS Land Surface
Reflectance 2015 were incorporated for a southern region along the El Salvador coast and Bay of
Jiquilisco Reserve.
High resolution imagery was used to analyze land cover change in the Monte Cristo
mangrove subset. Images from 07 October 2002 and 27 September 2006 were acquired from the
QuickBird satellite platform at a resolution of 2 meters. A mosaic image from 23 September and
28 October 2014 was acquired from the WorldView-2 satellite platform at a resolution of 1.84
meters. In all cases four bands, blue, green, red, and NIR, were used for image processing.
Figure 3 provides the timeline overlap of the data sources.
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Using supervised land classification methods, the three high resolution images for the
Monte Cristo were processed with ~8 training sample polygons for each desired land
classification. The land classifications used were water, forest, mixed vegetation, agriculture, and
open soil. The Maximum likelihood classification option was used to provide a quantitative
statistical analysis of each pixel radiance value to determine land type probability. Each date
provided a land classification map that could then be compared to the proceeding years and
create a temporal change trajectory. Figure 4 describes the land classifications.
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Results and Discussion
El Salvador’s southern Bay of Jiquilisco Reserve Mangrove Forest region yielded very few
fires during the time span of the acquired Landsat imagery for November 2004, October 2008,
and November 2015. With respect to November 2015, no fire data was available and in
November of 2004 and October 2008, only a total of four fires occurred all of which seemed to
be associated with agricultural controlled burning outside the protected area of the Bay of
Jiquilisco Reserve Mangrove Forest. Since there were so few fires occurring at such a small
scale, no regression analysis was conducted. An inference could be made that the drop in
agricultural percentage between November 2004 and October (2008) may have been a result of
agricultural burning and an increase in open vegetation see figure (). The minimal change within
the closed forest landscape percentage came as no surprise seeing that the Bay of Jiquilisco
Reserve Mangrove Forest is protected area. However, the low percentages of closed forest
landscape within the region appear to be indicative of prior time period when aggressive
deforestation could have occurred. Because of varying landscape percentages due to fires within
the study region, namely between open vegetation and agriculture, it remains imperative that a
conservation agriculture interface be implemented in order to safeguard each LCLU from any
possible detriments due to fire effects.
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Fires within the proximity of the Bay of Jiquilisco (2001-2015)
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The supervised classification of the Monte Cristo mangrove provides an opportunity to
visualize the gains and losses of land cover over the twelve year. With this gain and loss
analysis, the percentage of change is calculated based on pixel value difference. Within this time
frame we see an overall increase in water, at 31%, and an overall decrease in forest, at 13%.
Mixed vegetation grows as well at 27% but agriculture shrinks at 13%. Open soil remains
constant through the study period. Figure 6 shows the gain and loss areas within the imagery and
the tabulated graphed data based on the gain and loss analysis.
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Figure 7 provides an overview of the fire pattern within El Salvador as it relates to
MODIS collected fire plots and detected land cover. The primary location of fires are detected
with woody grassland, cropland, and cropland/natural vegetation mosaic.
Within the 14-year time period from 2001 to 2015, only 13 fires were detected within the
Monte Cristo mangrove. Based on national and regional patterns, a higher frequency of fires
would be expected. However, a low frequency of fires are observed within the mangrove. This
could be attributed to the land management practices of the communally controlled lands. We
see that the majority of fires detected happen within the December-February fire season, with a
small minority outside of the season. The fires out of season could be attributed to lightning
strikes or to a local hunting practice that uses fire to flush out game. Figure 7 highlights these
seasonal and non-seasonal plots.
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The majority of fires occur within forest cover, which is consistent with previous studies
on forest fires and fire management data. Of the 13 fires, 7 occurred in the forest. Three are
detected in agricultural or open fields, which is again consistent with prior studies (Southworth et
al. 2001). It is he three fires that occur at the interface of the forest-agriculture or forest-mixed
vegetation that is of interest, which is seen in figure 8. These fires could be indicative of fire
being used as a deforestation tool to expand existing agricultural lands. This highlights one of the
greater threats to the mangrove forest.
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Land cover change continues to occur within the Bahí de Jiquilisco reserve. There has
been measurable decrease in forest area within the Monte Cristo mangrove with a high increase
in water. Fire practices within El Salvador are similar to regional patterns. Fire patterns within
the Reserve, specifically the Monte Cristo mangrove, show some similarities but have low
frequency. This is likely a result of biosphere protection strategies driven by community
management practices,
Development by month's Useful for policy makers in that the data analysis serves as an
initial assessment when attempting to address the scope of fire effects within a particular region
within Central America the subsequent effect on a local region’s critical habitat or ecosystem.
Free use to the public or policymakers.
Increases in water identified is an interesting change in the landscape. Potential reasons
deserving further exploration include sea level rise, increased storm events, and the local practice
of actively clearing the natural channels through the mangrove forest. An increase in temporal
resolution could also provide additional data through more specific pattern analysis. An
exploration of land use policies at the national, state, and local levels may also provide insight
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into the management practices and enforcement success of mangrove preservation. Additionally,
an analysis of fire intensity at detected plot points may also provide indicators of land cover
change, as high intensity fires consume all biomass at an event site and lowers the probability of
site recovery or regeneration.
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