Forest Fires, Ecological Concerns and Fire Supression

Forest Fires, Ecological Concerns and Fire Suppression

The United States Forest Service designates “critical biological areas,” which are protected to a great extent against human impacts.  These zones are designed to conserve ‘species-at-risk;’ which are defined as being ‘specifically identified under the Endangered Species Act as threatened or endangered, and/or by the NatureServe global conservation status ranking system as being in jeopardy of extinction’ (Stein et al., 2010).  Balancing forest fire fuel reduction and fire prevention efforts, with the need to conserve particular areas for the benefit of certain species is often a difficult task.  In this report I have considered sources with varying viewpoints on critical biological areas; some arguing in support of critical area species protection, as well as those which see this status as a hindrance to fire management.  As I will show, careful planning aided by the powerful tool that is GIS can provide an effective route forward in combating, and planning for forest fires. 

The United States government spends millions of dollars per year combating forest fires across millions of hectares of forest.  Active fire suppression started in the United States around 1886.  Soon after the creation of the National Parks, the U.S. Army was tasked with patrolling the parks for fire suppression surveillance purposes.  Soon thereafter, serious discussions took place wherein key figures such as the second U.S. Forest Service Chief Henry Graves made a strong case for serious fire suppression policy.  Preemptive under burning to reduce fuel levels was encouraged; a policy he believed was based on traditional Native American Indian fire techniques (Stephens & Ruth, 2005).  Clearing of fuel is a key method of forest fire suppression and damage control.  The idea is that by removing dead, low-lying material from the forest floor, fires will spread less quickly, and be easier for fire fighters to control.  The Stephens and Ruth report stresses the necessity of comprehensive forest fire management techniques, as simply removing as much fuel as possible is not efficient.  Factors such as weather and topography play an important role in determining the best course of fire prevention action, and can dictate whether or not removing fuel from certain areas is efficient or even necessary.  Managing a complex web of data inputs and producing intuitive and coherent display of factor interaction is a challenging task; one which can be nigh on impossible without the use of GIS.

The creation of fire danger maps using GIS software is instrumental in planning regional forest fire management.  GIS has the power to overlay many data inputs in a single map projection; illuminating the interactions and interdependence of many levels of fire suppression techniques.  A 1996 article by Chuvieco & Salas appearing in the International Journal of Geographical Information Science elaborates on the importance and utility of GIS mapping in forest fire prevention, using a case study in Central Spain.  Chuvieco & Salas show how they used GIS mapping to create an inclusive model of forest fire factors, and provided an in depth and comprehensive report for the Spanish fire prevention service.  Factors such as climate play a large role in forest fire prevention.  Most weather monitoring is done in urban areas, at low elevations, which provides little to no useful data for the concerned rural forest regions.  Chuvieco & Salas use interpolation of local climate data and prefabricated climate maps to create relatively accurate weather data across large regions of forest.  This can be overlaid with data on topography, historical fires, soils, vegetation, fire lookout towers, fire stations, fire roads, etc.  The end result was to create a GIS fire danger model for the region.  The end product ‘danger map’ included seven factors; “air temperature, humidity, slope, aspect, fuel types, exposure of fuel types, and human fire risk,” (Chuvieco & Salas 1996).  The authors had to create their own digital elevation model (DEM) of the region, which was done by digitizing from a 1:50,000 scale map of the study area, and performing a linear interpolation to create the elevation raster.  GIS danger mapping is useful, but to create thoughtful fire prevention policy, factors other than simple forest fire risk must be considered.  This is especially true in the case of controlled fuel burns, in regards to their impact on local ecosystems. 

Fires effect local forest ecosystems greatly.  Not only do fires dramatically change the landscape, but the lack of fires due to vigilant fire prevention can also have negative impacts on biodiversity and species richness.  In many regions, including the section of forest in Los Angeles which was torched in the 2009 Station Fire, frequent small scale forest fires are a natural part of the ecosystems.  These fires cause the natural succession and diversity of habitat necessary to maintaining a healthy landscape.  When humans artificially suppress wildfires, some species find themselves with little to no habitat left, as they rely on new growth, and without forest fires, thick undergrowth with tough subshrubs dominate the landscape.  While active forest fire prevention decreases the frequency of forest fires, there may be a tendency for fires to be larger and more devastating when they do happen.  Without frequent fires, local flora and fauna populations are prone to disastrous declines when fires do strike (Stein et al., 2010).  The implications of forest fires on species richness become especially poignant in the case of critical biological areas.  These are areas which have been designated by the United States Forest Service as containing at-risk species, and are afforded special protections therefore.  However, this can become a point of contention between conservationists, and fire prevention advocates. 

Controlled burning of old growth forest fire fuel has for decades been the standard method of fire prevention on forest lands.  This becomes tricky when biologically sensitive zones come into play.  Some argue that without fire prevention work in these areas, there will be an unacceptable risk of property damage due to fire, and that the protected status of these lands is a hindrance to productive fire prevention activities.  T. L. Hanes 1971 work on ecological succession in Southern California’s chaparral landscape sheds light on the natural patterns and possible management techniques for fire prevention in the region.  Hanes observes that between the San Gabriel and San Bernardino mountains, there are relatively few widespread or abundant plants.  He also finds that succession is slowest on the south facing slopes, desert and oceanic exposure areas respond differently to post fire succession, etc.  A Los Angeles Times article, appearing on April 7, 2012 by Louis Sahgun explores the efficacy of replanting forest lost in the 2009 Station Fire.  He finds that the planted trees have by in large died off; out-competed by the natural succession of chaparral plants.  Attempts at restoring forest in a Mediterranean climate are yet another attempt by humans at taming the landscape, and as we have seen, have little to no positive effects.  Natural succession patterns are vital for supporting ecosystems, and anthropogenic fires, lack of fires, and forest restoration are all ecologically deleterious.  Observations such as those described in Hanes’s work are crucial to creating intelligent and comprehensive fire prevention policy.  These factors can be included in a GIS model as layers, and can direct fuel clearing or fire line creation in more efficient and biologically sound directions. 

Keeley, Morais and Fotheringham’s 2002 work historic fire regime in Southern California shrub lands provides an unbiased, and scientific view on fire prevention work.  They find that according to the California Statewide Fire History Database, the intense fuel clearing efforts of the past decades has had little to no effect on fire frequency or total area burned per year.  Fire intensity has not increased, and fire season has not changed since 1910.  They point to the high velocity winds of Southern California often will overshadow the ability of fuel clearing at fire spread reduction.  If you look at the map I have created of the spread of the 2009 Station Fire, you will see the distinct North and East progression of the fire; directly following wind patterns in the area, regardless of fire suppression attempts.  The leading determinate in forest fire ignition and spread, is the ever expanding “urban-wildland interface.”  Keeley, Morais and Fotheringham recommend focusing on strategic locations for fire prevention work, as opposed to broad spectrum fuel clearing fire rotations across a widespread area.  They point to landscape features, and suggest creating defensible buffer zones around at-risk areas.  Later, in 2002, Keeley and Fotheringham published another report on southern California fire regime.  In this report, they compare historic fire regimes in Southern California, and Northern Mexico, as these two regions are historically similar, but in contemporary times, California has undertaken massive fire prevention projects, while Mexico has not.  They find that there is actually little to no difference between the regions, and that it is human encroachment on wild areas which has led to increasing property damage, fire ignition and fire prevention expenditures.

My research has led me to believe that preemptive fuel clearing is not a good solution for fire prevention in the Station Fire area.  Those who wish to continue clearing fuel in the Station Fire area, irrespective of the critical biological areas which are affected by such activities are misinformed.  They are relying on outdated information and practices.  Instead, creation of comprehensive GIS maps, which can guide fire prevention officials to find defensible fire line locations, while avoiding disturbance of endangered species is recommended.  I have created a series of maps which illustrate the parameters of the 2009 Station Fire, the elevations and topography of the region, as well as critical biological areas in the region.  With these maps, fire prevention officials will be able to plan prevention projects around endangered species, while concentrating their efforts and funds on more strategic locations. [Maps located below reference list]

References

Chuvieco, E., & Salas, J. (1996). Mapping the spatial distribution of forest fire danger using GIS. International Journal of Geographical Information Science, 10(3), 333-345.

Hanes, T. L. (1971). Succession after fire in the chaparral of southern California. Ecological monographs, 27-52.

Keeley, J. E., & Fotheringham, C. J. (2002). Historic fire regime in southern California shrublands. Conservation Biology, 15(6), 1536-1548.

Keeley, J. E., Fotheringham, C. J., & Morais, M. (1999). Reexamining fire suppression impacts on brushland fire regimes. Science, 284(5421), 1829-1832.

Sahagun, L. (2012, April 07). Reforestation not taking hold in land burned by Station fire. The Los Angeles Times. Retrieved  March 17, 2013. <http://articles.latimes.com/2012/apr/07/local/la-me-dead-trees-20120408>

Stein, S. M., Carr M. A., McRoberts, R. E., Mahal, L. G., & Comas, S. J. (2010). Threats to At-Risk Species in America’s Private Forests. USDA Forest Service Northern Research Station State and Private Forestry: General Technical Report NRS-73.

Stephens, S. L., & Ruth, L. W. (2005). Federal forest-fire policy in the United States. Ecological Applications, 15(2), 532-542.

Reference map for concerned Southern California area.

Digital Elevation Model of concerned area.  This can be used to determine fire spread around landscape features, and promising locations of fire lines and fuel clearing efforts.

This map depicts the spread of the Station Fire.  From 2:48 am on August 29th, to 12:39 am on September 2nd.  Notice the South-North, and West-East spreading pattern of the fire.

This map depicts the fire fighter stations near the Station Fire area. This is overlayed with a Digital Elevation Model, so as to facilitate easy fire management planning and strategizing.

This map is arguably most relevant to this essay. It depicts the critical biological ares in the region of the Station Fire, along with a DEM and the historic perimeter of the Station Fire.  It is to be used in planning fire prevention efforts, especially as far as preemptive burning of fire fuel is concerned.  

Week 8 Lab- Population data

Creating visual representations of demographic data would be next to impossible without the powerful tool that is GIS.  Prior to the advent of this software technology, maps such as these would have to have been shaded in by hand, whilst paying close attention to the data as you worked.  Now I can easily input spreadsheet data and instantaneously have a clear, accurate and visually pleasing display of the data.  Even more importantly, I can update the data very quickly, maybe even in real time.  While I don't know how to link live data into a GIS map yet, it seems like a real possibility and an exiting tool for monitoring changes in spatial data. 

Asian population in the United States seems to be concentrated on the west coast, and more generally, in city centers.  I assume this has to do with the fact that the west coast is closer to Asia than the east coast.  Interestingly, Asians represent the fastest growing demographic in the United States; soaring 43% between the years 2000 and 2010 [News America Media, 2011].  I wonder if this trend continues, will we see more Asians in rural areas, or will the population distribution remain constant with the growth?  I theorize that the distribution would remain about constant, as many Asian immigrants come for higher education, and urban employment opportunities, as opposed to rural work such as farming.  

This map I find to be the most striking of the three I have included here today.  This is because of the heavy bias toward the west and south west areas, with relatively little showing in the eastern half of the country.  Diversity is the greatest along the coasts, especially in cities.  I assume that the concentrations in this demographic have to do with cities, more so than regions, as there are often small communities or groups of people of the same origins found in cities.  If data was available on a city level, and not just a county level, I would be able to corroborate this hypothesis by showing ethnic communities within the larger cities or towns.  GIS is an invaluable tool for analyzing population data; I would never have guessed how great a representation of some other race alone there is in Texas without it.  

Black population seems to be heavily concentrated in the south and southeast United States.  Is this because of the origins of Africans in the US?  Back in the days of slavery, most of the Africans were set to work in the same region that can be seen as having the highest concentration of black population today.  Having personally grown up in an area that was largely Black, I find this quite interesting.  My high school was 60% Black and 20% Latino.  Apparently this was actually uncommon across the west coast.  However, if you look closely at the San Francisco bay area, you will find a remarkably high percentage of Blacks.  This has to do with the mass migration of Black people from the south and southeast to the San Francisco bay during WWII, when there was a need for factory workers in the Richmond ship yards.  While the factories are long gone, the Black demographic remains remarkably high, and now there is actually a poverty crisis among the black population in this area.  My GIS map illustrates this trend simply, and poignantly reminds me of the history of African Americans in this country. 

Week 7 DEM

3D Model of Data area with elevation delineated by color gradient

Digital Elevation Models or DEMs are extremely useful in creating accurate maps of hilly areas.  I used the data provided on the course website, and as such, I do not know what the area is called where the data came from.  I do however know the coordinates of the map area, as I was able to recall them using the source data of my provided DEM data set.  The extent of my data is as follows: 39.384-39.829 degrees north; 104.969-105.789 degrees west.  My areas is a mountainous area wherein there is a steep elevation change as the mountains taper off into a valley, lake, river or ocean.  Below are maps I have created.  Hillshade demonstrates the elevation model with hills shaded such as in a topographical map.  Slope demonstrates the degree of slope, or the steepness of the terrain.  I have overlaid it on top of my original DEM data, so as to give the viewer an accurate depiction of the region.  Lastly, I have created an Aspect map, which shows the direction in which each of the slopes face.  This data could be used in development work, as the slope, and the aspect will to a greater extent determine the potential land use of the area.

Week 6 Lab- map projections

Map projections display the spherical earth on a two dimensional plane.  Transferring this data can be difficult, as some information will be lost in the process.  Different methods of map projection can yield differing data.  Different projections will keep certain aspects of the spherical data accurate, such as distance or area.  Depending on the intended use, certain map projections will be appropriate for differing situations.  For example, an ocean going vessel would not want to use an equal area projection, as this angles, direction and distance; possibly misleading the ship and its crew into a perilous situation.  Conformal maps would be most appropriate for navigation purposes (except in air travel, when an equidistant map should be used) as they preserve angles and local directions.

Equidistant maps could be used to calculate the total distance traveled by the aforementioned ship.  This would be best accomplished with a two point equidistant map, as opposed to an azimuthal projection, which bases its scale from a single point.  My examples of equidistant maps are both azimuthal.  The first centers on the North Pole, while the second centers on the coordinate origin, or where the equator and prime meridian intersect. 

Equal area maps are what they sound like; maps which preserve the correct ratio of land area.  These are useful for displaying data such as land use, or population density where the data is more about spatial distribution then exact distances or angles.  Distance can vary greatly between various equal area projections, as exemplified by my two equal area maps here shown.  The first is a Lambert Cylindrical projection, and shows the distance between Washington DC and Kabul, Afghanistan as being 10,108 miles.  The second is a Lambert Azimuthal equal area projection, which centers on the North Pole.  The Azimuthal projection however, shows the distance between Washington D.C. and Kabul, Afghanistan as being only 6,806 miles.  That is a 3,300 mile difference, which is more than the distance from San Francisco to New York City. 

My Mercator maps are conformal.  They could be used in my ship example for navigation and plotting purposes, as they preserve angles and represent constant navigations lines and allow the captain to stay the course.  I had trouble finding difference between the various Mercator projections, as all the ones I tried seemed to render similar or identical maps.  

Lab 4: ArcGIS Tutorial Map

Using ESRI's ArcGIS for the first time was an exciting and new experience for me.  I have never before had the opportunity to use this powerful piece of software.  Getting familiar with the interface was not as easy as I had anticipated.  Even with ESRI's detailed instructions for the tutorial, I often found my map different or dissimilar from the instructions.  For example, while creating the three maps required by this assignment I had difficulty making the map fit the data frame.  I did not understand the tools used for zooming, as there are many zoom options in the tool bars at the top.  There are page zoom (layout zoom) options for adjusting the view of the entire sheet, as well as data zoom options.  At multiple stages of the tutorial, I thought I had made an error and would have to start again, as my map would become very small within the data frame, or even disappear all together.  By the end of the tutorial however, I had come to understand the zoom functions, and was able to position my maps within their respective data frames with ease.

Another issue I had with using ArcGIS was not with the software itself, but rather with the remote desktop log in.  After many attempts at using the after hours log in, I was finally able to connect to a desktop computer in our computer lab.  However, even when I had achieved a stable connection, I was unable to load my map from my flash drive successfully.  As the computer lab is not open on the weekends, I resigned myself to finish the lab on Monday when the computer lab reopened.  Fortunately, my roommate and I came to Young Research Library today to study for upcoming midterms.  I sat at a desk which happened to have a desktop computer installed, and after a few hours of studying, an idea donned on me; what if the library computers also have ArcGIS installed on them?  Well it turns out they do, and I was able to complete my mapping tutorial as seen above.

Using ArcGIS for the first time taught me more than a few lessons.  Firstly, this software is not as simple, or easy to learn as I had anticipated.  I consider myself to be somewhat of a computer nerd, and I enjoy using Adobe Photoshop, and 3D CAD modeling software in my spare time.  Seeing as these programs are also considered to have a steep learning curve, and I had a relatively easy time learning them, I did not believe ArcGIS would prove as complicated or intriguing as it turned out to be.  I also manage eDiscovery data for legal firms as a job, which entails a large amount of database manipulation and management.  I hope that my experience in that field will help me with ArcGIS, but since we were given data to use in the tutorial, I have yet to see if that assumption will prove true.  This first taste of ArcGIS left me impressed, and excited to use the software for more challenging projects in the future.  As of right now, I am fully planing on completing the GIS minor here at UCLA.

I also thought of a few potential pitfalls as I use ArcGIS in the future.  Foremost among them, is my tendency to become so distracted by one detail, that I forget about the big picture and/or managing other details simultaneously.  For instance, while I was manipulating the final layout for my tutorial map production, I inadvertently shifted one of my maps without shifting the legend or scale along with it.  I was so distracted by editing one of the other maps, that I almost did not catch my error prior to exporting the map sheet for upload.  Little errors such as this will cost me points in this and future GIS classes, and may well cost me a job post graduation.  There are also several exciting potentials for my use of GIS in my current job as an eDiscovery and practice support contractor.  As we learned in class, most data contains location information, and this holds true in the legal field as well.  Many of the cases I have worked on deal with geographical distribution of class members, instances of liability and electronic address information.  I have yet to see a law firm hire a GIS contractor specifically; most often the task of creating visual representations of data falls on the practice support department, which does not staff any GIS professionals.  Once I become more proficient with ArcGIS, I can introduce GIS to my employers.  Hopefully I will be able utilize the software in creating powerful visual representations and even help formulate location based arguments for use in mediation and maybe even in trial.  Ideally, my future GIS skills will lead to more employment opportunities, and the potential for raises and promotions within my current position.

On another note, I was encouraged by this week's assignment to try and purchase a copy of ArcGIS from ESRI with which I could complete coursework at home, and also use for my own personal projects.  However, I was not able to find any retailers of the software, and ESRI's website did not list any pricing information.  The website simply said to call and inquire, which leads me to believe that ArcGIS is a rather expensive, and exclusive piece of software.  I would be interested to learn about any opportunities for students to purchase their own copy from ESRI, ideally at a discounted price!

Lab 3, Neogeography

     This week I have used Google Maps to create an interactive map of recommended places to go fly fishing in northern California.  The map utilizes points of interest, written explanations of each point, regional delineation, links to related web pages, photographs and videos.  My map is intended for fly fishing enthusiasts who are new residents and/or visitors to California.
Click HERE for the interactive map.

     Neogeography is a new trend in geography wherein anybody can create their own maps using open source and user friendly tools such as Google maps.  This can be quite useful in a number of instances.  For example; giving directions; highlighting important aspects of a region for a specific group, industry, or organization; creating 'sharable' lists of places by category, such as good places to eat, shop, go hiking, etc.  Businesses which historically could not afford to hire GIS professionals can now create their own custom interactive maps.  Neogeography allows more maps to be updated in real time.  As the world is constantly undergoing changes, traditional cartographers and/or GIS professionals would not be able to enter the same volume of data as the 'crowd-sourcing' methods of neogeography.
     There are however some drawbacks and pitfalls associated with this neogeography.  Everyone and anyone has access to the technology.  This leaves room for lots of error, and subsequent dissemination of misinformation.  At best this could be misleading; at worst leaving people stranded.  Like 'wiki' sources, maps created by amateurs should not be trusted, or cited when researching.  Moving forward, neogeography has the potential to allow for the creation of an unprecedented amount of crowd sourced mapping data which can be collected and analyzed.  Map based research will flourish, however as I have stated, caution must be taken.  With an open mind and an incredulous attitude, neogeography will be a very powerful tool. 

Lab 2: USGS Topographic Maps

1. Quadrangle title: BEVERLY HILLS, CA 1995

2. Adjacent quadrangles: N. VAN NUYS QUADRANGLE; NE. BURBANK; E. HOLLYWOOD; SE. INGLEWOOD; S. VENICE; SW. UNKNOWN; W. TOPANGA

3. First Version Created: 1966

4. Datum used to create the map: National Geodetic Vertical Datum of 1929; Horizontal datum- North American Datum of 1927 (NAD 27) 1000 meter grid; North American Datum of 1983 (NAD 83) adjustment via dashed corner ticks

5. Map Scale: 7.5 minute; 1:24,000

6. a) 5cm on the map is equivalent to 1200 meters on the ground.  b) 5 inches on the map is equivalent to 1.89 miles.  c) One mile on the ground is equivalent to 0.378 inches on the map.  d) Three kilometers on the ground is equivalent to 12.5 centimeters on the map.

7. Contour interval: 20 feet

8. Approximate geographic coordinates: a) Public Affairs Building 34°4'0" N, 118°26'30" W [34.067° N, 118.442° W] / b) Santa Monica Pier 34°00'38" N, 118°30' W [34.012° N, 118.5° W] / c) Upper Franklin Canyon Reservoir 34°7'00" N, 118°24'00" W [34.117° N, 118.400° W]

9.  Approximate elevations: Greystone Mansion 600 feet or 183 meters; Woodlawn Cemetery 160 feet or 49 meters; Crestwood Hills Park 740 feet or 226 meters.

10. UTM zone: 11

11. UTM coordinates from lower left corner: 3763000m easting, 362000m northing

 12. There are 1000000 square meters contained within each cell of the UTM gridlines.

13.

14. There is a 14°/249 MILS magnetic declination on this map.

15. East, from higher elevation to lower elevation

16.