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/ : ISSUES : DATA SETThe Invasive Grass-Fire Cycle in the U.S. Great Basin
Jennifer K. Balch1,2,5, Marnie K. Carroll3, and Bethany A. Bradley4
1 - National Center for Ecological Analysis & Synthesis, University of California, Santa Barbara, Santa Barbara, CA 93101-3351
2 - The Pennsylvania State University, Department of Geography, University Park, PA 16802
3 - Din College, Shiprock, NM 87420
4 - University of Massachusetts-Amherst, Amherst, MA 01003
5 - Corresponding Author: Jennifer K. Balch
( HYPERLINK "jkbalch@psu.edu" jkbalch@psu.edu)
THE ECOLOGICAL QUESTION:
How does cheatgrass (Bromus tectorum) alter fire regimes in the Great Basin?
ECOLOGICAL CONTENT:
invasive species, cheatgrass (Bromus tectorum), fire ecology, disturbance, spatial analysis tools
WHAT STUDENTS DO:
Design hypotheses about how an invasive plant species may alter fire behavior.
Explore NASAs data archive and download some of the large, publicly available datasets, specifically the MODIS burned area product.
Perform basic statistics using Excel, including creating linear regression lines, interpreting R-squared values, and conducting t-tests.
Perform basic spatial processing steps and analysis using ArcGIS, including using zonal statistics and reclassify tools.
Compare analysis and conclusions from both local field-based data and regional satellite data.
STUDENT-ACTIVE APPROACHES:
Students will be actively engaged through the exercises, which require students to conduct data analysis and answer questions using field-based data and satellite data. The exercises can be done in pairs to facilitate group learning and problem-solving. The module includes a number of short-answer questions designed to help students interpret fire data, as well as an in-class HYPERLINK "http://tiee.esa.org/teach/teach_glossary.html" \l "minute" minute paper, HYPERLINK "http://tiee.esa.org/teach/teach_glossary.html" \l "thinkpair" think-pair-share exercise, and a take-home essay at the conclusion of the module. The HYPERLINK "http://tiee.esa.org/teach/teach_glossary.html" \l "minute" minute paper is an active-learning exercise, which gives students only a couple minutes to write an essay in class, with the intention to generate quick feedback and resolve any confusion. The HYPERLINK "http://tiee.esa.org/teach/teach_glossary.html" \l "thinkpair" think-pair-share exercise is designed to give students a minute to think on their own, before discussing major concepts or ideas with their nearest neighbor, and then sharing with the whole class. In addition the lab exercises can be split so that two groups can work on separate parts of the problem. If you want to split the exercises for multi-group work Lab 1 can be split into two manageable sets: Part I (questions 1-5); and Part II (questions 6-9). In Lab 2, the first set of questions build through a necessary set of processing steps, but the last few questions are designed to be more open-ended allowing students to explore the data and design their own testable questions. A third lab has been designed for advanced GIS students.
SKILLS:
Students will acquire skills in: navigating dataset repositories, manipulating large data sets, reading metadata, creating maps and graphs using GIS (Geographic Information Systems) and statistical tools, and connecting data analysis to scientific concepts.
ASSESSABLE OUTCOMES:
In addition to the active learning approaches conducted in class, there are several take-home essay questions designed to measure student skills and intended learning outcomes.
The following questions can be asked pre- and post- module to determine how much students have learned from the exercises: What controls fire? And how can invasive plant species change fire behavior. In addition, the third advanced GIS lab can be used to gauge student acquisition of the introduced GIS techniques.
TRANSFERABILITY:
This teaching module is designed for undergraduates with some introduction to ecology or environmental science. Students should also have some knowledge of GIS and basic statistics, including exposure to descriptive statistics, t-tests, and linear regression. If students have no GIS experience, then the first part of the module can be conducted (i.e., up through the Whisenant data exercise). The exercises require some familiarity with Excel and ArcGIS programs.
SOURCE:
MODIS Burned Area Maps: May-September 2005
MODIS Burned Area Product (MCD45A1 product):
HYPERLINK "http://modis-fire.umd.edu/Burned_Area_Products.html" http://modis-fire.umd.edu/Burned_Area_Products.html
HYPERLINK "http://modis-fire.umd.edu/BA_getdata.html" http://modis-fire.umd.edu/BA_getdata.html
Description of MODIS Burned Area Product (Non-technical):
HYPERLINK "http://modis.gsfc.nasa.gov/data/dataprod/nontech/MOD14.php" http://modis.gsfc.nasa.gov/data/dataprod/nontech/MOD14.php
Description of MODIS Burned Area Product, Metadata (Technical):
HYPERLINK "http://modis-fire.umd.edu/BA_usermanual.html" http://modis-fire.umd.edu/BA_usermanual.html
If you wish to download the original, publically-available data: HYPERLINK "ftp://ba1.geog.umd.edu/" ftp://ba1.geog.umd.edu/
Username: user
Password: burnt_data
Folder: TIFF > Win03 > 2005
Save GEOTIFF files:
MCD45monthly.A2005121.Win03.005.burndate.tif (May 2005)
MCD45monthly.A2005152.Win03.005.burndate.tif (June 2005)
MCD45monthly.A2005182.Win03.005.burndate.tif (July 2005)
MCD45monthly.A2005213.Win03.005.burndate.tif (August 2005)
MCD45monthly.A2005244.Win03.005.burndate.tif (September 2005)
Note, these are the raw burned area data for the conterminous U.S. These images have been clipped and processed to be used in this module. See description of datasets below for full details on files provided for this module.
OVERVIEW OF THE ECOLOGICAL BACKGROUND
This module has been designed to teach a couple major themes at the intersection of fire ecology and invasive species biology, principally the relationship between invasive species and altered fire behavior.
The overall goal is to get students to design hypotheses about how invasive plants change fire behavior and then test these hypotheses using field-based and satellite-based data. Students will compare conclusions from both sets of data and will critically think across scales and types of data. The purpose of the full module is to get students to understand how cheatgrass alters fire activity, and to gain analysis skills that allow them to apply the techniques to a slightly different situation.
This module has been designed for a full 7-hour day (but can be made into lecture/lab combo see sample agenda). There are two lectures included, the first introduces the basics of fire ecology, fuel properties, and the role of invasive plants in changing fire regimes. The second introduces satellite-based fire data. And there is a third optional lab for more advanced GIS work.
Note this is also an active research question, and although the conclusions for this TIEE are preliminary, students should know that they are participating in an active program that should have future results and publications to draw on in the future.
REFERENCES
D'Antonio, C. M., and P. M. Vitousek. 1992. Biological invasions by exotic grasses, the grass-fire cycle, and global change. Annual Review of Ecology and Systematics 23:63-87.
Brooks, M.L., C.M. DAntonio, D.M. Richardson, J.B. Grace, J.E. Keeley, J.M. DiTomaso, R.J. Hobbs, M. Pellant, D. Pyke. 2004. Effects of invasive alien plants on fire regimes. Bioscience 54: 677-688.
Notes on this paper: DAntonio and Vitousek (1992) is the seminal paper that reviewed how invasive grasses can alter fire activity (at time of this module it has been cited over 900 times). Overall, the way in which invasive species alter ecosystem-level processes is fairly unknown, yet this paper provided a key insight into similar changes observed across ecosystems. This key paper identifies the geographic patterns of grass invasion, the ecological effects of grass invasion, and how grass invasion can lead to changes in fire regimes. Last, the authors identify and explore case studies from across the globe. This paper sets that stage for students to begin to ask how an invasive species can alter the systems that it is introduced to, and they should be able to identify key mechanisms that enable invasive grasses to change fire activity with the information provided here. An alternative, more recent review paper, is Brooks et al. 2004 in the journal, Bioscience.
W h i s e n a n t . 1 9 9 0 . C h a n g i n g r e f r e q u e n c i e s o n I d a h o s S n a k e R i v e r p l a i n s : e c o l o g i c a l a n d m a n a g e m e n t i m p l i c a t i o n s . S y m p o s i u m o n c h e a t g r a s s i n v a s i o n , s h r u b d i e - o f f , a n d o t h e r a s p e c t s o f s h r u b b i o l o g y a n d m a n a g e m e n t . I n t e r m o u n t a i n R e s e a r c h S t a t i o n , O g d e n , U T , Las Vegas, NV.
Notes on this paper: Whisenant (1990) was the first to quantify how cheatgrass increases fire activity, and he found that with cheatgrass fire frequency in sagebrush ecosystems increased from every 60110 years to every 35 years. He used data from field sites in the Snake River Plains in Idaho. By measuring fuel properties of cheatgrass and other native fuels, and then comparing with observed historical fire frequencies he was able to estimate this very high frequency of fires associated with the introduction of this non-native grass. This paper is cited often as the classic example of clear-cut changes in fire activity. Using the data from this paper and comparing it with the remote-sensing data offers students the perspective of how you can get companion answers using data collected at different scales.
Bradley, B.A., and J. Mustard. 2008. Comparison of phenology trends by land cover class: a case study in the Great Basin, USA. Global Change Biology 14, 334346.
Notes on this paper: Bradley and Mustard (2008) explain the technique used to develop the landcover map that is used in the optional, third lab.
See these additional resources:
Cheatgrass (Bromus tectorum): HYPERLINK "http://www.invasive.org/browse/subinfo.cfm?sub=5214" http://www.invasive.org/browse/subinfo.cfm?sub=5214
USGS Great Basin Project: HYPERLINK "http://www.usgs.gov/features/greatbasin/overview/greatbasin.html" http://www.usgs.gov/features/greatbasin/overview/greatbasin.html
NASAs Earth Observing System for educators: HYPERLINK "http://eospso.gsfc.nasa.gov/eos_homepage/for_educators/index.php" http://eospso.gsfc.nasa.gov/eos_homepage/for_educators/index.php
DATA SETS
The following datasets are for two exercises. The first exercise requires field-based data from the Whisenant 1990 paper ( HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/faculty.xlsx" faculty.xlsx and HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/students.xlsx" students.xlsx). The second requires satellite-based burned area and cheatgrass data, and a shapefile of the western U.S. Note, the Excel files also include a second sheet with the analysis steps for the satellite data after the processing part of the exercise has been completed in ArcGIS. This information is repeated in the student instruction section. The third, optional lab requires an additional shapefile which is the vegetation classification of the U.S. Great Basin.
i. Snake River Plains data
Data from the Snake River Plains on fire frequency, fuel characteristics, and species that make up those fuels are provided from a paper published by Whisenant in 1990. See original paper for a description of the sampling methods and a description of the site locations. A script for exploring and analyzing this data in R has been provided ( HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/script_cheatgrassfiretiee.R" script_cheatgrassfiretiee.R), some prior knowledge of the statistical program R is required to use this script. Alternatively, the data file can be opened and analyzed in the Excel sheet (cheatgrassfire_exercise_forteachers.xlsx and cheatgrassfire_exercise_forstudents.xlsx).
The headings in the data file are the following:
site = location of sampling
fire_freq = fire frequency (fires/year)
fuel_cover = fine fuel cover (percent), measured within 10x10 cm quadrats
fuel_mass = fine fuel mass (lb/acre)
cheat_dom = whether cheatgrass (Bromus tectorum) is listed as the first, dominant species contributing to fuels
ii. Processed MODIS burned area files for the module:
May 2005: HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/monthly_bd_UTMClip_A2005121.tif" monthly_bd_UTMClip_A2005121.tif
June 2005: HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/monthly_bd_UTMClip_A2005152.tif" monthly_bd_UTMClip_A2005152.tif
July 2005: HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/monthly_bd_UTMClip_A2005182.tif" monthly_bd_UTMClip_A2005182.tif
August 2005: HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/monthly_bd_UTMClip_A2005213.tif" monthly_bd_UTMClip_A2005213.tif
September 2005: HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/monthly_bd_UTMClip_A2005244.tif" monthly_bd_UTMClip_A2005244.tif
The values of the numbers in the file indicate the following:
0 = unburned
1-366 = approximate Julian day of burning
900 = snow or high aerosol
9998 = water bodies, internal
9999 = water bodies, seas and oceans
10000 = not enough data to calculate
iii. Cheatgrass Distribution Map
This unpublished cheatgrass map is from a single MODIS scene of northern Nevada. The projection is the same as for the MODIS burned area product. This classification was done by Bethany Bradley, using methods similar to the map produced for Bradley and Mustard 2008. This map is based on inter-annual variability in cheatgrass phenology between 2005-2002 springs. The map detects 75% of cheatgrass 'presence' points with a 20% false positive rate. Overall accuracy is around 78%.
File: HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/cheatgrass_map.tif" cheatgrass_map.tif
The values of the numbers in the file indicate the following:
0 = no cheatgrass
1 = cheatgrass presence
iv. State Outlines of Western USA
This shapefile gives the state outlines for the western USA region of interest. Projection matches the cheatgrass map and MODIS burned area product.
File: HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/WesternUSA_ProjectUTM.zip" WesternUSA_ProjectUTM.zip
v. Vegetation classification of the U.S. Great Basin
This shapefile contains the classification map derived by Bradley and Mustard (2008), and is used in the optional third lab.
The values in the GRIDCODE are for the following CLASS vegetation types:
1 Agriculture
2 Non-vegetated
3 Montane Shrub/grass
4 Pinyon-Juniper
5 Alkali Meadow
6 Salt Desert Shrub
7 Cheatgrass
8 Sagebrush Shrub
File: HYPERLINK "http://tiee.esa.org/vol/v8/issues/data_sets/balch/resources/decision_tree_classification_avhrr_utm.zip" decision_tree_classification_avhrr_utm.zip
STUDENT INSTRUCTIONS
Introduction
People have altered natural fire regimes across landscapes for tens of thousands of years by changing ignitions and fuels ADDIN EN.CITE Pyne20011699169916996Pyne, S.J.Fire: A brief history2042001SeattleUniv. of Washington PressLocation: SML, Stacks, LC Classification
Call Number: GN416 P85X 2001 (LC)
Status: Not Checked OutAmazon(Pyne 2001). In the last couple hundred years, people have even altered the plant species that make up those fuels. One remarkable feedback is the introduction of invasive grass species across continents which then changes fire activity. This process is termed a novel grass-fire cycle ADDIN EN.CITE D'Antonio199253353353317D'Antonio, C. M.Vitousek, P. M.STANFORD UNIV,DEPT BIOL SCI,STANFORD,CA 94305.
DANTONIO, CM, UNIV CALIF BERKELEY,DEPT INTEGRAT BIOL,BERKELEY,CA 94720Biological invasions by exotic grasses, the grass-fire cycle, and global changeAnnual Review of Ecology and SystematicsAnnu. Rev. Ecol. Syst.Annual Review of Ecology and SystematicsAnnu. Rev. Ecol. Syst.Annual Review of Ecology and SystematicsAnnu. Rev. Ecol. Syst.63-8723alien species, land-use change, competitive effects, ecosystem processes, grass-fueled firesmesembryanthemum-crystallinumconservation biologysecondary successionamazon deforestationnitrogen limitationprosopis-glandulosatussock grassesseedling growthnorth-carolinanative prairie1992ISI:A1992JZ28100004DISS; Amazon, pasture grasses341(D'Antonio and Vitousek 1992).
In the western U.S., cheatgrass (Bromus tectorum) has invaded the Great Basin biome. Introduced in the mid-1800s, this single species with origins in north Africa and the Middle East, now dominates 20,000 km2 ADDIN EN.CITE Bradley200524752475247517Bradley, B. A.Mustard, J. F.Identifying land cover variability distinct from land cover change: Cheatgrass in the Great BasinRemote Sensing of EnvironmentRemote Sensing of EnvironmentRemote Sens. Environ.204-21394220050034-4257WOS:000226270800005Grass-fire cycle; Cheatgrass(Bradley and Mustard 2005). The large-scale presence of cheatgrass has altered natural fire regimes, particularly in sagebrush and salt desert shrub ecosystems ADDIN EN.CITE Chambers200726712671267117Chambers, J. C.Roundy, B. A.Blank, R. R.Meyer, S. E.Whittaker, A.What makes Great Basin sagebrush ecosystems invasible by Bromus tectorum?Ecological MonographsEcological MonographsEcol. Monogr.117-14577120070012-9615WOS:000245603900007cheatgrassWhisenant199025712571