home > data and maps > derived data > MSO predicted habitat details

ForestERA Data Layer Overview - Mexican Spotted Owl Nesting Habitat

Description

This is a layer representing predicted nesting habitat for the Mexican Spotted Owl (Strix occidentalis lucida), as well as a measure of nesting habitat quality, across the assessment area. The layer was built using a combination of simple rules based on a literature review, and Mahalanobis distance based on habitat conditions at known nest sites. The layer has a resolution of 90m (0.8 ha or 2 acres), and values within the layer range from zero to 5. Higher values indicate a higher degree of habitat suitability.

Purpose

This data layer was created as part of the ForestERA project to support landscape-scale forest restoration planning efforts by a broad group of stakeholders including federal and state agencies, academic institutions, and non-governmental entities. These data are intended for regional analyses over spatial extents on the order of tens to hundreds of thousands of acres, and were not developed for use at finer spatial scales, although they may be useful for some applications at finer scales.

Development

We chose two modeling approaches to optimize the use of available information on Mexican Spotted Owl. First, because previous studies documented characteristics of nesting habitat for these species, we used rules developed from the literature to identify the extent of potential nesting habitat on the landscape. This involved a search of the literature to identify a set of variables related to nesting habitat and a range of possible threshold values that might be used to identify areas most likely to support nesting pairs of these raptors. Second, we employed the Mahalanobis distance statistic (hereafter M-distance) to generate a dataset that could be used as a surrogate for habitat “suitability” or “preference”. Georeferenced locations of 132 nest sites for Mexican Spotted Owl were obtained from the United States Forest Service Rocky Mountain Research Station and the United States Fish and Wildlife Service for use in the modeling effort.

To identify potential nesting habitat, we used publications that described habitat characteristics around Mexican Spotted Owl nest sites (Grubb et al. 1997, May & Gutierrez 2002; Seamens & Gutiérrez 1995), breeding season roost sites (Ganey & Balda 1994; Young et al. 1998, Zwank et al. 1994) and current management guidelines (USFWS 1995) to choose a range of threshold values (Prather et al., in review). Since owsl are tied primarily to pine-oak and mixed-conifer habitats, we initially created a “preferred vegetation” layer with these two vegetation types identified as “habitat”. While areas of pure ponderosa pine are not typically used by owls for nesting (USFWS 1995) we included areas identified as ponderosa pine in immediate proximity (1 pixel or 90m) of pine-oak and mixed conifer to include ecotonal areas between habitat types that may have been misclassified using the ETM imagery. Finally, we included areas of pure ponderosa pine on steep slopes (>8o) because owls have some affinity for areas with high slope (Ganey & Balda 1989a; Zwank et al. 1994), and in our vegetation mapping we found that it was difficult to distinguish pure pine from mixed-conifer or pine-oak on slopes >8o using ETM imagery (ForestERA unpublished data). We then eliminated patches of habitat smaller than 40 ha because these patches would likely be too small to be suitable for nesting (USFWS 1995).

After delineation of potential nesting habitat, we used M-distance and habitat characteristics at Mexican Spotted Owl Nest sites to develop an index of habitat suitability within potential nesting habitat. M-distance has been used frequently in mathematics and physics to compare the similarity of datasets, but is rarely used in ecology (e.g., Clark et al. 1993; Corsi et al. 1999; Knick and Dyer 1997). M-distance is a multivariate statistic that provides a measure of dissimilarity between two multivariate datasets (Farber & Kadmon 2003). In this effort, one dataset is the mean vector of habitat characteristics at known Mexican Spotted Owl nest sites while the other dataset is the range of conditions across the entire landscape (Prather et al., in review). The "distance” for any location on the landscape represents the dissimilarity between conditions at that location and the mean habitat conditions at the known nest sites. This value is scaled in multivariate space using the covariance between the measured habitat conditions at the locations used by the species (Clark et al. 1993).
We used dominant overstory vegetation, canopy cover, basal area, tree density, slope, and the sine and cosine derivatives of aspect as predictor variables for our M-distance modeling effort. We determined values for each of these variables at Mexican Spotted Owl nest sites by extracting the values from the GIS raster layers using the “zonal statistics” function in ArcGIS Spatial Analyst (ESRI Corporation). We overlaid the nest locations with the raster layers of the predictive variables and determined the value of each raster layer in the pixel corresponding to the nest location. Analysis of characteristics of the 90m (0.81ha) pixel in which each nest fell was deemed appropriate since other studies have shown significant patterns between nest site selection by large raptors and habitat characteristics at scales of approximately 0.5 - 1ha (e.g., McComb et al. 2002). For purposes of developing the M-distance model we used 2/3 (82) of the nest sites as training data and the remaining 1/3 (41) of the nest sites were withheld for accuracy assessment.

The final habitat layer represents a combination of our two modeling efforts. We classified this layer into 5 categories for purposes of display, analysis, and dissemination. The zero category represents areas not predicted to be suitable for nesting habitat using our simple rules. The remaining 4 categories represent areas of increasing similarity to the mean habitat characteristics at Mexican Spotted Owl nest sites based on M-distance. Fifty percent of nest sites would be expected to fall into category 4, an additional 25% into category 3, an additional 15% into category 2, and the final 10% into category 1.

Accuracy Assessment

To test the effectiveness of using threshold values within predictor variables as a means of identifying potential habitat, we used Chi-squared goodness of fit tests (Zar 1999) to determine whether the potential habitat models did significantly better at predicting locations of Mexican Spotted Owl nests than chance alone. For this analysis we used the entire set of nest sites (n = 132). This analysis suggested that significantly more (111 or 84%) nest sites fell within the predicted extent of potential nesting habitat than would be expected by chance alone (v = 2, X² = 92.2, P < 0.0001).

To test whether the M-distance statistic was effective at identifying the locations of nest sites, we used Chi-squared goodness of fit tests to determine whether the M-distance statistic accurately predicted the number of nests within the test datasets that fell within the portion of the predicted habitat in each of the four categories identified above. For these analyses we used the 1/3 of the nests (n = 44) that were not used as training data for the M-distance model. This analysis showed that the distribution of nests within each habitat category fit the expected distributions (v = 3, X² = 1.02, P = 0.80; Table 1). This suggests that the simple rules did a good job at defining potential habitat, and that M-distance was effective at predicting the area within potential habitat where a given percentage of nests would be expected to occur.

Table 1: Distribution of Mexican Spotted Owl nests (n = 44) in the test dataset in relation to categories generated using Mahalanobis distances and the nests in the training datasets.

Sources of errors

The potential habitat model developed above contained about 85% of the known Mexican Spotted Owl nest sites. There are several potential reasons that some sites may fall outside of predicted habitat. First, there is some uncertainty in the basal area and vegetation type layers used in the modeling. Thus some areas that are suitable habitat may not be identified as such. Second, many of the owl nest sites had positioning errors of + 100m, so the location of some nests on the landscape may be inaccurate. Third, conditions may have changed at some nest sites since they were last active. All of these may lead to errors.

It should also be noted that certain assumptions must be made when using the M-distance statistic as a measure of habitat “quality” or “preference”. The most important of these assumptions are that the distribution of habitat characteristics at known nest sites is representative of the actual distribution of nest sites, and that the mean habitat characteristics at nest sites represent “optimal” or “preferred” habitat characteristics. We do not currently have the data to determine whether M-distance values can be linked to survivorship or reproductive success, and thus we do not know how good an estimator of habitat quality is provided by the M-distance statistic.

Recommendations

We recommend that this layer be used at a minimum resolution of 90m (0.8 ha or 2 acres) for purposes of analysis and display. However, ForestERA data layers were not designed for analyses at the level of individual pixels, and uncertainty in the data will generally decline over greater spatial extents. Therefore, we recommend using larger analysis units, with groupings of at least 50 cells (40 ha or 100 acres). Finally, we reiterate that ForestERA data layers were developed for the purpose of regional landscape-level planning, and we suggest that the analyses be applied over spatial extents of tens to hundreds of thousands of acres. We recognize, however, that this layer may be useful for analyses over smaller spatial extents depending on the type and purpose of those analyses.

Literature Cited

Clark, J. D., J. E. Dunn, and K. G. Smith. 1983. A multivariate model of female black bear habitat use for a Geographic Information System. Journal of Wildlife Management 57: 519-526.

Corsi, F., E. Dupre, and L. Boitani. 1999. A large-scale model of wolf distribution in Italy for conservation planning. Conservation Biology 13: 150-159.

Farber, O. and R. Kadmon. 2003. Assessment of alternative approaches for bioclimatic modeling with special emphasis on the M-distance. Ecological Modelling 160: 115-130.

Ganey, J. L. and R. P. Balda. 1994. Habitat selection by Mexican Spotted Owls in northern Arizona. Auk 17: 162-169.

Grubb, T. L., J. L. Ganey, and S. R. Masek. 1997. Canopy closure around nest sites of Mexican Spotted Owls in northcentral Arizona. Journal of Wildlife Management 61: 336-342.

Knick, S. T. and D. L. Dyer. 1997. Distribution of Black-tailed Jackrabbit habitat determined by GIS in southwestern Idaho. Journal of Wildlife Management 61: 75-85.

May, C. A. and R. J. Gutierrez. Habitat associations of Mexican Spotted Owl nest and roost sites in central Arizona. Wilson Bulletin 114: 457-466.

McComb, W. C., M. T. McGrath, T. A. Spies, and D. Vesely. 2002. Models for mapping potential habitat at landscape scales: an example using Northern Spotted Owls. Forest Science 48: 203-216.

Prather, J. W., J. L. Ganey, P. Beier, W. M. Block, M. Ingraldi, J. Jenness, Y. Xu, H. M. Hampton, and T. D. Sisk. (in review). Simple models successfully map nesting habitat for two raptors in southwestern coniferous forests. Conservation Biology.

Seamans, M. E. and R. J. Gutiérrez. 1995. Breeding habitat characteristics of the Mexican Spotted Owl in the Tularosa Mountains, New Mexico. Condor 97: 944-952.

U. S. Fish and Wildlife Service (USFWS). 1995. "Recovery plan for the Mexican Spotted Owl (Strix occidentalis lucida)." U. S. Fish and Wildlife Service, Albuquerque, New Mexico.

Young, K. E., R. Valdez, P. J. Swank, and W. R. Gould. 1998. Density and roost site characteristics of Spotted Owls in the Sierra Madre Occidental, Chihuahua, Mexico. Condor 100: 732-736.

Zar, J. H. 1999. Biostatistical Analysis, 4th Edition. Prentice-Hall Inc. Englewood Cliffs, New Jersey.

Zwank, P. J., K. W. Kroel, D. M. Levin, G. M. Southward, and R. C. Romme. 1993. Habitat characteristics of Mexican Spotted Owls in southern New Mexico. Journal of Field Ornithology 65: 324-334.

Contact us for data

Last updated March 4, 2005