Species Habitat and Analysis
Data Set
and Name |
Description |
Temporal Resolution |
Temporal Extent |
Spatial Resolution |
YERC-PSW |
Percent Surface Water |
8-day |
2000-2011 |
500 m |
CASA_Express |
Net Primary Productivity (NPP) |
Daily/Monthly |
2000-2011 |
500 m |
CASA_Express |
Aboveground herbaceous (forage) biomass |
Daily/Monthly |
2000-2011 |
500 m |
CASA_Express |
Litter biomass |
Monthly |
2000-2011 |
500 m |
CASA_Express |
Potential & Estimated Evapotranspiration (PET/EET) |
Daily/Monthly |
2000-2011 |
500 m |
CASA_Express |
Surface water in inundated soil layer |
Monthly |
2000-2011 |
500 m |
CASA_Express |
Surface water in soil organic layer |
Monthly |
2000-2011 |
500 m |
CASA_Express |
Surface water in top mineral soil layer |
Monthly |
2000-2011 |
500 m |
CASA_Express |
Surface water in lower mineral subsoil layer |
Monthly |
2000-2011 |
500 m |
CASA_Express |
Snow Water Equivalent (SWE) |
Monthly |
2000-2011 |
500 m |
YERC-FragChg |
Fragmentation and Change Detection GIS layers |
Annual |
2001-2011 |
30 to 250 m |
YERC-CASA |
Moderate to extreme drought – user specified |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Urban Expansion |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Agriculture Expansion – New Irrigated Cropland |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Agriculture Expansion – CRP for two years or more |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Wetland Conversion to cropland |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Wetland Loss (drained or dried out) |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Wetland Expansion |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Fires (non-forest) |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Fires (forested) |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Insect kill (forested) |
Annual |
2000-2011 |
250 m |
RMA-MODIS |
Logging (forested) |
Annual |
2000-2011 |
250 m |
UM-FzThw |
Freeze-Thaw Parameters (Frozen/Thawed/Transition) |
Twice Daily |
1979-Present |
25 km |
NASA-TOPS |
Minimum Temperature |
Daily |
1955-2009 |
1 km |
NASA-TOPS |
Maximum Temperature |
Daily |
1955-2009 |
1 km |
NASA & NCEP |
Precipitation |
Daily |
1955-2009 |
1 and 32 km |
NASA-TOPS |
Shortwave Solar Radiation |
Daily |
1955-2009 |
1 km |
NASA-TOPS |
Vapor Pressure Deficit (VPD) |
Daily |
1955-2009 |
1 km |
NASA-MODIS |
Land Surface Temperature (LST) |
8 day |
2000-2010 |
1 km |
NASA-MODIS |
Land Cover Type (Coarse scale) |
Annual |
2001-2010 |
500 m |
NASA-MODIS |
Normalized Difference Vegetation Index (NDVI) |
16 day |
2001-2010 |
1 km |
NASA-MODIS |
Enhanced Vegetation Index (EVI) |
16 day |
2001-2010 |
1 km |
NASA-MODIS |
Fraction Photosynthetically Active Radiation (FPAR) |
8 day |
2001-2010 |
1 km |
NASA-MODIS |
Leaf Area Index (LAI) |
8 day |
2001-2010 |
1 km |
NASA-MODIS |
Gross Primary Production (GPP) |
8 day |
2001-2010 |
1 km |
YERC has used remote sensing data products in the analysis of species (legacy observations and monitoring) and habitat condition in many studies. Immediately below are recent publications and below that are short reports of species analysis currently being completed.
Potter, Christopher, Steven Klooster, Robert Crabtree, Shengli Huang, Peggy Gross, and Vanessa Genovese. 2011. Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling. Carbon Balance and Mangement 6:3-19
Sheldon, J.W., R.L. Crabtree, C.S. Potter, B. Winkelman, and D. Weiss. 2011 (in press). Snow Dynamics and Mountain Fox (Vulpes vulpes macroura) in Yellowstone: Incorporating Climate in Species-Habitat Models. The 10th Biennial Scientific Conference on the Greater Yellowstone Ecosystem. William D. Ruckelshaus Institute of Environment and Natural Resources. University of Wyoming, Laramie, WY.
Crabtree, R. L. and J.W. Sheldon. 2011 (in press). Monitoring and modeling environmental change in Protected Areas: Integration of focal species populations and remote sensing. Chapter 21 in Remote Sensing of Protected Lands, Y.Q. Wang, (ed.). Taylor and Francis, Boca Raton, FL
Weiss, Daniel, Katie Gibson, Jennifer Sheldon, and Robert Crabtree. 2011. The Customized Online Aggregation & Summarization Tool for Environmental Rasters (COASTER) system. Accepted. International Journal of Geographical Information Science
Geremia, Chris, P. J. White, Rick L. Wallen, Fred G. R. Watson, John J. Treanor, John Borkowski, Christopher S. Potter, and Robert L. Crabtree. 2011. Accepted. Predicting Bison Migration out of Yellowstone National Park using Bayesian Models. PLoS ONE 6(2): e16848. doi:10.1371/journal.pone.0016848
Hatala, Jaclyn, Michael Dietze, Robert Crabtree, the Interagency Whitebark Pine Monitoring Working Group, Katherine Kendall, Diana Six, and Paul Moorcroft. 2011. An ecosystem model of white pine blister rust (Cronartium ribicola) spread in whitebark pine (Pinus albicaulis) of the Greater Yellowstone Ecosystem. Ecological Applications, 21:1138–1153.
Barnowe-Meyer, Kerry, P.J. White, Troy L. Davis, Douglas W. Smith, Robert L. Crabtree, and John A. Byers. 2010. Influences of wolves and high-elevation dispersion on reproductive success of pronghorn (Antilocapra americana). J. Mammalogy 91(3): 712-721.
Hatala, J.A., K. Q. Halligan, R. L. Crabtree, and P. M. Moorcroft. 2010. Landscape-scale patterns of forest pathogen damage in the Greater Yellowstone Ecosystem. Remote Sensing of Environment 114: 375-384.
Crabtree, Robert, Chris Potter, Randall Mullen, Jennifer Sheldon, Shengli Huand, Joshua Harmsen, Ann Rodman, and Cathie Jean. 2009. A modeling and spatio-temporal analysis framework for monitoring environmental change using NPP as an ecosystem indicator. Remote Sensing of Environment 113: 1486-1496.
White PJ, TL Davis, KK Barnowe-Meyer, RL Crabtree, and RA Garrott. 2007. Partial Migration and Philopatry of Yellowstone Pronghorn. Biol. Cons. 135: 518-526.
Lynch HJ, Moorcroft PR, Crabtree RL, and Renkin RA. 2006. The Influence of Previous Mountain Pine Beetle (Dendroctonus ponderosae) Activity on the 1988 Yellowstone Fires. Ecosystems 9(8):1318-1327.
Moorcroft PR, Lewis MA, Crabtree RL. 2006. Mechanistic Home Range Models Predict Spatial Patterns and Dynamics of Coyote Territories in Yellowstone. Proceedings of the Royal Society B 273(1594):1651-1659.
Short Reports
Sage Grouse
Sage Grouse (Centrocercus urophasianus) in western Wyoming have moved into an era of co-habitation with energy development. Over the past 10 - 15 years natural gas extraction in the region has drastically altered the landscape of this region of Wyoming. The nesting habitat of the sage grouse has been highly fragmented by the construction of all the drill and well pads as well as the roads leading into them. This has changed the habitat space that these ground nesting birds have available to them.
The Upper Green River Basin (UGRB) is a region in southwest Wyoming that lies between the Wind River mountain range to the east and the Wyoming range to the west. The UGRB, also known as the Pinedale anticline, contains the upper reaches of the Green River and its tributaries running south through it as well a few small scale developed low-density/semi-urban areas interspersed throughout. This geologic region is and has been under heavy energy development for more than a decade due to its rich deposits of natural gas in two fields (Pinedale and Jonah) underlying a large portion of this area. The valley bottomland is a critical habitat for sage grouse nesting as well as the home of these two active and growing gas extraction operations. The area of focus is a moderately varied landscape and includes mostly sagebrush and high desert vegetation habitat as well as some irrigated croplands and riparian areas with minimal urban interface involved.
This study was conducted to test the RSPF code on an example data set, as proof of method for assessing environmental factors hypothesized to relate to sage grouse nest site selection. This particular focus brings into relief a particular life history stage critical for population regulation, so we focus here on the techniques for investigation of environmental/landscape covariates and their relationship to nesting habitat. Sage grouse are known to have particularly high historic fidelity to nest in and around areas where they were born. Sage grouse females (‘hens’) prefer these steppe sagebrush and high desert ecosystems for nesting and raising young. With this study we want to explore readily available geophysical and climatological data as well as modeled covariates derived largely from NASA data and data products for patterns and trends in nest site selection of sage grouse.
The response data used in this exploratory/proof of method analysis is a dataset that spans the years 2000 – 2005 and is (x, y) locations of nests. The dataset is a compilation of field observed nesting sites found by tracking radio collared sage grouse hens across the study period. Due to the implicitly sensitive nature of nest data for sage grouse, the analysis method can be run by the biologist on a laptop, and are not specified for publication.
Black-Necked Cranes
The Tibetan plateau contains the largest population of black-necked cranes (Grus nigricollis); requiring wetlands during all phases of their annual cycle – breeding, migration, and wintering. Freshwater lakes and associated wetlands, riverine systems and their associated marshes, and wet meadow complexes are all available and used by cranes at different times of the year (various papers cited in Collar et al. 2001). The black-necked crane and its wetland breeding habitats continue to face an array of conservation challenges, the most significant being environmental change resulting from Land Use/Land Cover (LULC) change and climate change; the black-necked crane remains a rare species, with a total world population of only around 11,000 birds. (http://www.savingcranes.org/surveyrevealsthreatenedblackneckedcraneincreasingintibet.html).
The black-necked crane was a great test species on the RSPF tool using only NASA derived data sets in this RSPF analysis over a foreign landscape. A data set containing 51 observed black necked crane locations was used along with four other input data sets: shuttle radar topography mission (SRTM) elevation data set, MCD12Q2 MODIS Land Cover Dynamics, MOD13A3 MODIS Enhanced Vegetation Indices (EVI) and MCD15A2 MODIS Leaf Area Index (LAI) data sets were used in the Tibetan Plateau RSPF analysis. See RSPF manual for how the tool performs the analysis and a description of results.
Indiana Bat
Populations of the Indiana bat (Myotis sodalis) are declining across their range, prior to the detection of White Nose Syndrome (see Figure 1). In order to add to understanding of drivers of population change in this species, we undertook a preliminary analysis with the goal of gaining insight into the potential influences of climatic conditions on Indiana Bat population trajectories. Our objectives here are twofold: first we identify optimal spatiotemporal zones (“windows”) for each stage of Indiana bat life history, and second we relate population trajectories to the selected windows in an effort to understand environmental drivers associated with specific life history stages.
Bison Migration 2010
Long distance migrations by ungulate species often surpass the boundaries of preservation areas where conflicts with various publics lead to management actions that can threaten populations. We chose the partially migratory bison (Bison bison) population in Yellowstone National Park as an example of integrating science into management policies to better conserve migratory ungulates. Approximately 60% of these bison have been exposed to bovine brucellosis and thousands of migrants exiting the park boundary have been culled during the past two decades to reduce the risk of disease transmission to cattle. Data were assimilated using models representing competing hypotheses of bison migration during 1990-2009 in a hierarchal Bayesian framework. Migration differed at the scale of herds, but a single unifying logistic model was useful for predicting migrations by both herds. Migration beyond the northern park boundary was affected by herd size, accumulated snow water equivalent, and aboveground dried biomass. Migration beyond the western park boundary was less influenced by these predictors and process model performance suggested an important control on recent migrations was excluded. Simulations of migrations over the next decade suggest that allowing increased numbers of bison beyond park boundaries during severe climate conditions may be the only means of avoiding episodic, large-scale reductions to the Yellowstone bison population in the foreseeable future. This research is an example of how long distance migration dynamics can be incorporated into improved management policies.
Mountain Fox
Snow pattern dynamics in northern temperate regions exert a critical regulatory role on a multitude of ecosystem processes. Snow cover onset and ablation, snow-water equivalent (SWE) patterning, snow-pack penetrance (over-snow travel; access to prey in the sub-nivean space), and timing of major snow events are all important to terrestrial animals. As climate patterns shift, changes in patterning of snow dynamics may exert important adaptational influences on animal ecology and energetic budgets. Snow data are available from remotely sensed, in situ measurements, and modeled estimates, but a consistent set of approaches for assessing the ecological impacts of changing snow metrics has not yet been realized. Access to standardized low/no-cost snow covariates for animal-habitat models remains an important goal that has ramifications for both management and research. We investigated the winter use patterns of mountain red fox (Vulpes vulpes macroura) on the northern range of Yellowstone National Park (YNP) and evaluated snow cover and SWE alongside more traditional habitat attributes. We found that SWE is an important determinant of habitat use by red fox on the northern range of YNP. Based on SNOTEL and observational data, we suggest that snow-hardening events may also play a key role for mountain fox foraging success in YNP and contribute to a mechanistic explanation for why SWE is important.
Arkansas Valley evening primrose (Oenothera harringtonii)
A rare and endemic plant in Colorado, the Arkansas Valley evening primrose (hereafter primrose) is distributed in southeastern portions of the state. The species is also known as Colorado Springs evening primrose and is ranked as vulnerable (Colorado Natural Heritage Program 2010) and sensitive (Ladyman 2005) based on state and federal conservation criteria. To our knowledge, no studies exist about the distribution and ecology of the primrose, and the best data available on ecological factors affecting its occurrence are from a 2005 Conservation Assessment by the USFS (Ladyman 2005). The plant grows at an elevation of 1,400–2,000 m; on compacted silty clay, sandy, and silty loam soils; on flat to gentle slope topography; in areas of low vegetation cover (<20–50 %); and in full sun to partial shade. Average annual precipitation in primrose habitat is approximately 33 cm with most occurring between April – September. Populations are ephemeral such that plants are abundant in some years and scarce in others. Although high seed abundance and germination were recorded in wet years, the relationship between population fluctuations and environmental variables is unknown.
Swift fox (Vulpes velox)
The distribution of the swift fox (Vulpes velox) has been reduced in North America and, at one time, it was considered for listing as threatened under the endangered species act (Allardyce and Sovada 2003). Swift fox populations declined in Colorado, prompting the Colorado Division of Wildlife to form a swift fox conservation team that conducted monitoring of fox in the 1990s and 2000s (Finley et al. 2005, Martin et al. 2007). Conservation threats to swift fox populations include habitat destruction or modification, human-caused mortality such as harvest and collisions with vehicles, and natural mortality such as disease and predation (Allardyce and Sovada 2003).
Predation by coyotes (Canis latrans) is considered the main cause of natural mortality for swift fox, but several other species prey on the fox including golden eagles (Aquila chrysaetos), American badgers (Taxidea taxus), and red fox (Vulpes vulpes) (Sovada et al. 1998, Andersen et al. 2003, Karki et al. 2007). Habitats with dense, tall vegetation are considered marginal for the fox as they potentially hinder predator detection (Schauster et al. 2002). In Texas, swift foxes avoided irrigated agricultural and Conservation Reserve Program (CRP) lands, which authors partially attributed to the taller vegetation making it more difficult to detect predators (Kamler et al. 2003). In New Mexico, track stations situated in areas of relatively short vegetation were visited more often when compared to tall vegetation (Harrison and Schmitt 2003).
Swift foxes are generally found in relatively flat to gently rolling topography (Fitzgerald et al. 1994, Allardyce and Sovada 2003, Harrison and Whitaker-Hoagland 2003). In Wyoming, foxes were found more than expected in areas of ≤3% slope and less than expected in areas with slopes >3% (Olson 2000). Swift foxes are fossorial throughout the year and use dens in order to escape predators and extreme weather (Kitchen et al. 1999, Allardyce and Sovada 2003). Foxes have multiple dens and the distribution and density of dens is an important habitat requirement (Allardyce and Sovada 2003); for example in Colorado, individual foxes used ≥20 different dens within a period of about one year (Andersen et al. 2003). Several studies found that foxes prefer soils that facilitate den digging, including clay, clay loams, sandy loams, and loam soils (Jackson and Choate 2000, Harrison 2003, Harrison and Whitaker-Hoagland 2003, Kintigh and Andersen 2005).
Shortgrass habitats are believed to provide swift foxes with a diverse prey base, open terrain that permits predator detection, and soils that are suitable for den excavation (Allardyce and Sovada 2003). Indeed, swift foxes are considered shortgrass prairie specialists (Kamler et al. 2003), and in Colorado, (Finley et al. 2005) found a strong positive relationship between percent shortgrass prairie habitat and probability of swift fox occupancy.
Grasshopper Sparrow (Ammodramus savannarum)
Although widely distributed across North America, the grasshopper sparrow (GRSP; Ammodramus savannarum) can be uncommon to rare in parts of its range (Vickery 1996). Breeding Bird Surveys suggest that the species is declining throughout its range, mainly due to habitat loss from conversion of grassland prairie to agricultural lands (Vickery 1996, Kuenning, 1998). The sparrow is found in brushier habitats in the western portions of its range, and in Colorado it is found mostly in grass prairie habitats (Kuenning, 1998). In southern Quebec, sites used by GRSP had sparse and short vegetation with means of 17% bare ground and 24 cm vegetation height (Jobin and Falardeau 2010). The species is more likely to occupy contiguous habitat with patch area ranging from 1–100 ha depending on location (Delany et al. 1995, Vickery 1996, Jobin and Falardeau 2010). Drought is believed to negatively affect GRSP (Niemuth et al. 2008, Albright et al. 2010); however the relationship between precipitation and GRSP densities is not firmly established. For example, Niemuth et al. (2008) found GRSP abundance in North Dakota had a negative relationship with moisture, while Ahlering et al. (2009) found positive correlation between spring precipitation and sparrow densities in the same state.
Analysis of lesser scaup (Aythya affinis) resource selection in Yukon Flats National Wildlife Refuge
Lesser scaup (Aythya affinis) is among the most abundant species of waterfowl in North America. The range of this species of diving duck, including winter and summer habitat and migration routes, covers most of North America. Lesser scaup typically spend their winters in the southern United States and migrate to summer breeding grounds in northwest Canada and Alaska. Lesser scaup populations have declined by almost half since the early 1980s (Austin et al. 2000), making this a species of concern for wildlife managers. Identifying the factors contributing to population declines is challenging, however, due to the migratory nature of the birds and the vast area they may inhabit, particularly when migratory routes are considered. As such, factors that lead to mortality and/or reduced reproductive success may be associated with any or all of the areas in which the ducks spend their time (i.e., winter feeding grounds, summer nesting grounds, and along migratory routes).
Despite the complexity associated with researching population changes within a migratory species, several notable hypotheses have emerged as possible reasons for the decline in lesser scaup populations. These hypotheses have focused primarily on habitat conditions within summer sending grounds as a likely cause of lesser scaup population declines. This research attempts to characterize lesser scaup habitat preference within a landscape ecological perspective (i.e., by associating characteristics of the surrounding landscape with the number of lesser scaup present at sample locations). Associating lesser scaup counts with spatially and temporally variable environmental conditions has the potential to (1) provide a regional context in which to interpret results from fine-scale analyses, and (2) identify coarse-scale factors that may contribute to population declines.
Preliminary Analysis of Change in Greenness Onset in the Northwestern United States (1955-2009)
A statistical relationship was established between MODIS greenness onset data (MOD12Q2) (2001-2009) and variables derived from gridded climatic data covering five states in the northwestern United States (Washington, Oregon, Idaho, Montana, and Wyoming). Multiple variable combinations and model types were assessed before arriving at a model that was reasonably consistent across space and through time. Independent climatic variables in the final model consist of (1) the number of days the maximum temperature rose above freezing, (2) the accumulated daily maximum temperature, (3) the sum of perceptible water that fell as snow, and (4) the accumulated daily solar radiation. The resulting model was then applied to the full climatic dataset (1955-2009) to assess the change in the greenness onset date over the 55-year period for which there was data. The modeled results suggest that greenness onset is happening earlier throughout the region, but the change in greenness onset date is greatest in areas east of the continental divide, particularly in central Montana, and at higher elevations.
Regional contextualization of alpine treeline ecotones in the Greater Yellowstone Ecosystem
The Alpine Treeline Ecotone (ATE) is the boundary zone between closed-canopy subalpine forests and the highest individual trees or tree patches found upslope. In areas without major anthropogenic disturbances the ATE is principally a climatic boundary above which trees cannot tolerate one or more aspect(s) of the harsh alpine environment. The relationship between the ATE and climatic conditions has led to great public and scientific interest in the ATE as both a potential bellwether of, and a potentially at-risk area from, the effects of global climate change. These simplistic associations, however, mask the complex, spatially heterogeneous, and scale-dependent set of abiotic and biotic controls influencing the ecotone.
This research contextualizes ATEs in the Greater Yellowstone Ecosystem (GYE) by exploring characteristics of treelines found throughout the western United States. Of particular interest are climatic conditions and species composition, factors that strongly influence treeline elevations and vegetation patterns. The Beartooth Mountains and the Wind River Range are highlighted from a regional perspective to compare GYE ATE conditions with those found elsewhere. The regional analysis is coupled with preliminary results from a new project in the Beartooth Mountains exploring the influence of microclimatic conditions on tree establishment.
step or using the first day of the time step. Output options refers to the file type the SWE tools outputs the raster; 3 output file types are offered: GeoTIFF, ERDAS Imagine and ArcGRID.
Finally, transparency level that is displayed to the raster output, ranging from 0 to 100%, can be entered into the tool adjusting the transparency of the raster output so it can be viewed overtop of the elevation layer for ease of viewing the results. Once the date range, time step and output options have been entered into the model, the user can submit data and the tool will run the calculations on the parameters entered by the user; results will automatically be added to the existing display. Although the tool calculates snow water equivalence in millimeters, symbology for the raster output is converted to display centimeters of snow water equivalence represented by 4 classes: 0-50 cm, 50-100 cm, 100-150 cm and 150+ cm, respectively.
