ADDITIONAL REFERENCES
Modeling Habitat Suitability and Wildlife-Habitat Relationships
1. Adamus, P. R. 1995. Validating a habitat evaluation method for predicting avian richness. Wildl. Soc. Bull.
23(4):743-749.
Keywords: wetlands / forested wetlands / riparian habitat / birds / songbirds / nongame birds /
Colorado / West / models / habitat models / wildlife habitat relationship models / wildlife-habitatrelationship models / WHR models / habitat assessment / methods / techniques / biological diversity
/ biodiversity
2. Adamus, P. R., L. T. Stockwell, E. J. Clairain, Jr., M. E. Morrow, L. P. Rozad, and R. D. Smith. 1991.
Wetland Evaluation Technique (WET), Volume 1: literature review and evaluation rationale. U.S.
Army Corps of Engineers, Waterways Experiment Station. Wetlands Research Program Tech. Rep.
WRP-DE-2. Vii + 287pp.
Keywords: forested wetlands / wetlands / wildlife / WET / Wetlands Evaluation Technique / habitat quality / modeling / literature review / bottomland hardwoods
3. Akcakaya, H. R., M. A. McCarthy, and J. L. Pearce. 1995. Linking landscape data with population viability analysis: management options for the helmented honeyeater. Biol. Conserv. 73:169-176.
Keywords: landscape data / geographic information systems / GIS / spatial data / PVA / population viability analysis / minimum viable populations / extinction probability / modeling / life history analysis / helmented honeyeater / Lichenostomus melanops cassidix / demographic modeling / metapopulations / metapopulation analysis / Habitat Suitability Index models / HSI models / risk assessment
4. Alldredge, J. R., D. L. Thomas, and L. L. McDonald. 1998. Survey and comparison of methods for study of resource selection. Journal of Agricultural, Biological, and Environmental Statistics 3, no. 3: 237-
53.
Keywords: statistics / methods / techniques / resource selection / habitat use / habitat selection / habitat preference / habitat availability / compositional analysis / chi-square analysis / logistic regression / models / modeling / resource selection functions
5. Apps, C. D., B. N. McLellan, J. G. Woods, and M. F. Proctor. 2004. Estimating grizzly bear distribution and abundance relative to habitat and human influence. J. Wildl. Manage.
68, no. 1: 138-52.
Keywords: British Columbia / Canada / grizzly bears / Ursus arctos horribilis / predictive modeling / resource selection functions / predictive modeling / landscape ecology / population density / population abundance / Canada / distribution / human influence / DNA
6. Ball, L. C., P. F. Doherty, Jr., and M. W. McDonald. 2005. An occupancy modeling approach to evaluating a
Palm Springs ground squirrel habitat model. J. Wildl. Manage.
69, no. 3: 894-904.
Keywords: presence-absence information / presence / absence / site occupancy / modeling / models / detection / detection probability / methods / techniques / habitat use / resource selection functions / species distribution / species range / occurrence / habitat modeling / statistics / statistical analysis / indirect detection indices / detection indices / population estimation / California / Palm Springs ground squirrel / Spermophilus / small mammals / habitat conservation plans / habitat models
7. Bender, L. C., G. J. Roloff, and J. B. Haufler. 1996. Evaluating confidence intervals for habitat suitability models. Wildl. Soc. Bull. 24(2):347-352.
Keywords: Habitat Suitability Index models / HSI models / habitat modeling / habitat models / confidence intervals / error / bootstrapping / simulation / gray squirrels / Sciurus carolinensis / computer program / computer software
8. Benson, G. L., and W. F. Laudenslayer, Jr. 1986. DYNAST: simulating wildlife responses to forestmanagement strategies. Pages 351-355 in J. Verner, M. L. Morrison, and C. J. Ralph, Eds. Wildlife
2000, Modeling Habitat Relationships of Terrestrial Vertebrates. Univ. Wisconsin Press.
Keywords: modeling / modelling / habitat / relationships / relationship / birds / breeding birds /

songbirds / DYNAST / models / model / silviculture / forest management / National Forests
9. Best, L. B., and D. F. Stauffer. 1986. Factors confounding evaluation of bird-habitat relationships. Pages 209-
216 in J. Verner, M. L. Morrison, and C. J. Ralph, Eds. Wildlife 2000, Modeling Habitat
Relationships of Terrestrial Vertebrates. Univ. Wisconsin Press.
Keywords: modeling / modelling / habitat / relationships / relationship / songbirds / nongame birds / multivariate models / statistics / multivariate statistics / methods / techniques
10. Bettinger, P., J. Sessions, and K. Boston. 1997. Using Tabu search to schedule timber harvests subject to spatial wildlife goals for big game. Ecological Modeling 94, no. 1997: 111-23.
Keywords: Tabu search / harvest schedulers / timber harvests / spatially explicit models / models / modeling / habitat goals / Rocky Mountain elk / harvest scheduling
11. Block, W. E., M. L. Morrison, J. Verner, and P. N. Manley. 1994. Assessing wildlife-habitat-relationships models: a case study with California oak woodlands. Wildl. Soc. Bull. 22(4):549-561.
Keywords: habitat models / wildlife-habitat models / wildlife-habitat-relationships models / modeling / models / testing / verification / validation / amphibians / herpetofauna / birds / small mammals / California / methods / techniques
12. Breininger, D. R., V. L. Larson, B. W. Duncan, and R. B. Smith. 1998. Linking habitat suitability to demographic success in Florida scrub-jays. Wildl. Soc. Bull. 26(1):118-128 .
Keywords: Florida scrub-jays / Aphelocoma coerulescens / habitat suitability / demographics / demography / landscape patterns / remote sensing / sinks / sources / habitat use / habiitat models / nongame birds / breeding birds / resident birds
13. Brody, M., W. Conner, L. Pearistine, and W. Kitchens. 1989. Modeling bottomland hardwood forest and wildlife habitat changes in Louisiana's Atchafalaya Basin. Pages 991-1004 in R. R. Sharitz and J. W.
Gibbons, Eds. Freshwater Wetlands and Wildlife. DOE Symposium Series No. 61.
Keywords: wildlife / habitat / habitat use / diversity / density / species richness / forested wetlands / bottomland hardwoods / Atchafalaya Basin / modeling / models / FORFLO / simulation / forest succession / HSI / habitat suitability index models
14. Brooks, R. P. 1997. Improving habitat suitability index models. Wildl. Soc. Bull. 25(1):163-167.
Keywords: habitat suitability index models / HSI models / habitat models / modeling / validation / model validation / habitat assessment / forested wetlands / Louisiana waterthrush / Seirius motacilla / riparian habitat
15. Browning, D. M., S. J. Beaupre, and L. Duncan. 2005. Using partitioned Mahalanobis D
2
( k ) to formulate a
GIS-based model of timber rattlesnake hibernacula. J. Wildl. Manage.
69, no. 1: 33-44.
Keywords: timber rattlesnakes / Crotalus horridus / bootstrap / validation / cross-validation / habitat models / modeling / hibernacula / Mahalanobis D
2
( k ) / Mahalanobis distance / partitioned
Mahalanobis distance / methods / techniques / GIS / GIS-based model / Arkansas / Madison County
Wildlife Management Area / habitat use / Ozark Mountains / reptiles / snakes
16. Canterbury, G. E., T. E. Martin, D. R. Petit, L. J. Petit, and D. F. Bradford. 2000. Bird communities and habitat as ecological indicators of forest condition in regional monitoring. Conserv. Biol. 14(2):544-
558.
.
Keywords: nongame birds / songbirds / breeding birds / bird communities / ecological indicators / forest condition / monitoring / long-term monitoring programs / EMAP / Environmental Monitoring and Assessment Program / guilds / assemblages / overstory vegetation / canopy cover / basal area / habitat index / bird-community index / methods / techniques / logistic regression / predictive models
17. Capen, D. E., J. W. Fenwick, D. B. Inkley, and A. C. Boynton. 1986. Multivariate models of songbird habitat in New England forests. Pages 171-175 in J. Verner, M. L. Morrison, and C. J. Ralph, Eds. Wildlife
2000, Modeling Habitat Relationships of Terrestrial Vertebrates. Univ. Wisconsin Press.

Keywords: modeling / modelling / habitat / relationships / relationship / songbirds / nongame birds /
New England / multivariate models / statistics / multivariate statistics
18. Clark, J. D., J. E. Dunn, and K. G. Smith. 1993. A multivariate model of female black bear habitat use for a
Geographic Information System. J. Wildl. Manage. 57(3):519-526.
Keywords: black bears / Ursus americanus / habitat use / Geographic Information Systems /
Mahalanobis distance statistic / telemetry / radiotelemetry / roads / Arkansas
20. Clawson, M. E., T. S. Baskett, and M. J. Armbruster. 1984. An approach to habitat modeling for herpetofauna. Wildl. Soc. Bull. 12(1):61-69.
Keywords: herpetofauna / reptiles / amphibians / herptofauna / habitat use / models / modelling
21. Conner, L. M. 2003. A technique to locate isolated populations using satellite imagery. Wildl. Soc. Bull.
30, no. 4: 1044-49.
Keywords: satellite imagery / remote sensing / Bachman's sparrow / Aimophila aestivalis / songbirds
/ nongame birds / breeding birds / Georgia / habitat model / habitat use / Mahalanobis distance / monitoring / methods / techniques
22. Curtis, P. D., and P. G. Jensen. 2004. Habitat features affecting beaver occupancy along roadsides in New
York State. J. Wildl. Manage.
68, no. 2: 278-87.
Keywords: beaver / Castor canadensis / haitat / logistic regression / New York / highways / roads / presence / occupancy / predictive models
23. Dasgupta, N., and J. R. Alldredge. 1998. A multivariate
χ 2
analysis of resource selection data. Journal of
Agricultural, Biological, and Environmental Statistics 3, no. 3: 323-34.
Keywords: statistics / methods / techniques / resource selection / habitat use / habitat selection / habitat preference / habitat availability / GIS / Geographical Information Systems / models / modeling / resource selection functions / chi-square analysis / dependent observations / Columbian sharp-tailed grouse / Tympanuchus phasianellus columbianus
24. Davenport, D. E. 1994. A quantitative analysis of habitat quality for the red-cockaded woodpecker. M.S.
Thesis. North Carolina State Univ., Raleigh. 41pp.
Keywords: red-cockaded woodpeckers / Picoides borealis / habitat use / foraging habitat / reproduction / fitness / models / modeling
25. Davis, L. S., and L. I. DeLain. 1986. Linking wildlife-habitat analysis to forest planning with ECOSYM.
Pages 361-369 in J. Verner, M. L. Morrison, and C. J. Ralph, Eds. Wildlife 2000, Modeling Habitat
Relationships of Terrestrial Vertebrates. Univ. Wisconsin Press.
Keywords: modeling / modelling / habitat / relationships / relationship / succession / forest succession / forest structure / structure / ECOSYM / models / model / silviculture / forest management / National Forests / forest planning / spotted owl / Strix occidentalis / GIS / geographic information system
26. Dettmers, R. , and J. Bart. 1999. A GIS modeling method applied to predicting forest songbird habitat. Ecol.
Appl.
9, no. 1: 152-63.
Keywords: habitat use / habiat quality / songbirds / nongame birds / models / modeling / habitat relationship models / cerulean warbler / Dendroica cerulea / spatially explicit models / moisture gradients / cumulative distribution function / GIS / presence / topography / wood thrush / scarlet tanager / Ohio
27. Dettmers, R., D. A. Buehler, J. G. Bartlett, and N. A. Klaus. 1999. Influence of point count length and repeated visits on habitat model performance. J. Wildl. Manage. 63(3):815-823 .
Keywords: nongame birds / breeding birds / point counts / sampling / methods / techniques / length of time / duration / logistic regression / models / modeling / southern Appalachians / Tennessee / bird-habitat models / point count duration / model development

28. Dettmers, R., D. A. Buehler, and K. E. Franzreb. 2002. Testing habitat-relationship models for forest birds in the southeastern United States. J. Wildl. Manage.
66, no. 2: 417-24.
Keywords: habitat use / habiat quality / songbirds / nongame birds / models / modeling / habitat relationship models / Georgia / Tennessee / Virginia / Southeast / Southern Blue Ridge / southern
Appalachians / southern Appalachian Mountains / matrix model
29. Diefenbach, D. R., and R. B. Owen, Jr. 1989. A model of habitat use by breeding American black ducks. J.
Wildl. Manage. 53(2):383-389.
Keywords: American black ducks / black ducks / Anas rubripes / habitat use / modeling / linearlogistic model / beavers / Castor canadensis / habitat quality / wildlife habitat quality
30. Donovan, M. L., D. L. Rabe, and C. E. Olson, Jr. 1987. Use of geographic information systems to develop habitat suitability models. Wildl. Soc. Bull. 15(4):574-579.
Keywords: geographic information systems / GIS / information systems / systems / habitat suitability models / models / suitability models / methods / techniques / HSI models
31. Durham, D. B., R. K. Abernathy, D. C. Eagar, R. P. Ford, P. B. Hamel, L. J. O'Neil, and T. M. Pullen, Jr.
1988. Application of the habitat evaluation system to modeling bottomland hardwood forest communities in west Tennessee. Trans. N. Amer. Wildl. and Natur. Conf. 53:481-490. 53: 481-90.
Keywords: Habitat Evaluation System / bottomland hardwoods / forested systems / modeling / habitat modeling / habitat quality / methods / techniques / HES
32. Erickson, W. P., T. L. McDonald, and R. Skinner. 1998. Habitat selection using GIS data: a case study.
Journal of Agricultural, Biological, and Environmental Statistics 3, no. 3: 296-310.
Keywords: statistics / methods / techniques / resource selection / habitat use / habitat selection / habitat preference / habitat availability / GIS / Geographical Information Systems / moose / Alces alces / models / modeling / resource selection functions
33. Fecske, D. M., J. A. Jenks, and V. J. Smith. 2002. Field evaluation of a habitat-relation model for the
American marten. Wildl. Soc. Bull.
30, no. 3: 775-82.
Keywords: American marten / Martes americana / habitat-relationship model / habitat-relation model
/ models / modeling / Black Hills / South Dakota / track-plate-box survey / track plates / track boxes
/ surveys / habitat models / logistic regression / habitat use
34. Felix, A. B. , H. Campa, K. F. Millenbach, S. L. Panken, S. R. Winterstein, and W. E. Moritz. 2002.
Applications of using a landscape-scale model to quantify white-tailed deer habitat potential in
Michigan, U.S.A. Z. Jagdwiss 48, no. 2002: 107-14.
Keywords: model / habitat use / white-tailed deer / Odocoileus virginianus / habitat potential /
Michigan / browse / availability / forage / availability / browse quality / hard mast / forest structure / basal area / models / modeling
35. Felix, A. B., H. Campa, III, K. F. Millenbah, S. R. Winterstein, and W. E. Moritz. 2004. Development of landscape-scale habitat-potential models for forest wildlife planning and management. Wildl. Soc.
Bull.
32, no. 3: 795-806.
Keywords: habitat potential / habitat-potential models / landscape-scale models / landscape ecology / white-tailed deer / Odocoileus virginianus / land cover / habitat suitability models / forest structure
36. Finn, J. T., and R. Howard. 1979. Modeling a beaver population on the Prescott Peninsula, Massachusetts: feasability of Landsat as an input. Proc. Eastern Region Remote Sensing Conf. (Submitted). 8pp.
Keywords: beavers / Castor canadensis / Landsat imagery / satellite imagery / modeling / modelling / habitat / population modeling / simulation
37. Fleming, K. K., K. A. Didier, B. R. Miranda, and W. F. Porter. 2004. Sensitivity of a white-tailed deer habitat-suitability index model to error in satellite land-cover data: implications for wildlife habitatsuitability studies. Wildl. Soc. Bull.
32, no. 1: 158-68.

Keywords: white-tailed deer / Odocoileus virginianus / habitat suitability index models / HSI models
/ habitat suitability models / GIS / remote sensing / land cover / satellite imagery / classification / error / error propogation / habitat use / sensitivity
38. Garrison, B. A., R. A. Erickson, M. A. Patten, and I. C. Timossi. 2000. Accuracy of wildlife model predictions for bird species occurrences in California counties. Wildl. Soc. Bull.
28, no. 3: 667-74.
Keywords: habitat relationship models / models / modeling / validation / accuracy / nongame birds / birds / species distributions / California / habitat models
39. Gross, J. E. , M. C. Kneeland, D. F. Reed, and R. M. Reich. 2002. GIS-based habitat models for mountain goats. J. Mammal.
83, no. 1: 218-28.
Keywords: habitat use / models / modeling / GIS / geographical information systems / habitat models / habitat relationship models / logistic regression / mountain goats / Oreamonos americanus /
Colorado / escape cover / escape terrain / topography
40. Guisan, A., and N. E. Zimmermann. 2000. Predictive habitat distribution models in ecology. Ecological
Modeling 135, no. 2000: 147-86.
Keywords: models / modeling / vegetation models / habitat models / species models / habitatrelationship models / model calibration / GIS / methods / techniques / statististics
41. Haight, R. G. 1996. Wildlife models: predicting the effects of habitat restoration. J. For. 94(12):4-6.
Keywords: models / modeling / habitat restoration / GIS / geographic information systems / landscape structure / landscape configuration / population models / methods / techniques
42. Hatten, J. R., and C. E. Paradzick. 2003. A multiscaled model of southwestern willow flycatcher breeding habitat. J. Wildl. Manage.
67, no. 4: 774-88.
Keywords: birds / nongame birds / songbirds / Arizona / Empidonax traillii extimus / GIS / habitat use / habitat selection / neighborhood analysis / logistic regression / riparian habitat / predictive modeling / predictive models
43. Hoving, C. L., D. J. Harrison, W. B. Krohn, R. A. Joseph, and M. O'Brien. 2005. Broad-scale predictors of
Canada lynx occurrence in eastern North America. J. Wildl. Manage.
69, no. 2: 739-51.
Keywords: Canada lynx / Lynx canadensis / AIC / GIS / predictive models / landscape ecology / logistic regression / climate / snowfall / information-theoretic approach / Maine / habitat-relationship model / snowshoe hares / Lepus americanus
44. Howard, R. J., and J. S. Larson. 1985. A stream habitat classification system for beaver. J. Wildl. Manage.
49(1):19-25 .
Keywords: beavers / Castor canadensis / habitat use / discriminant analysis / principal components / modelling / models / population density / density / predicting
45. Hurme, E., M. Monkkonen, A. Nikula, V. Nivala, P. Reunanen, T. Heikkinen, and M. Ukkola. 2005. Building and evaluating predictive occupancy models for the Siberian flying squirrel using forest planning data. Forest Ecology and Management 216, no. 2005: 241-56.
Keywords: occupancy models / boreal forests / habitat suitability / Siberian flying squirrel /
Pteromys volans / Finland / Europe / forest planning / models / modeling
46. Jaberg, C., and A. Guisan. 2001. Modelling the distribution of bats in relation to landscape structure in a temperate mountain environment. J. Appl. Ecol.
38: 1169-81.
Keywords: bats / Chiroptera / modeling / modelling / habitat use / canonical correspondence analysis
/ Europe / Switzerland / Jura mountains / generalized linear models / habitat models / habitat modeling
47. Jacoby, C., A. L. Foote, and L. A. Johnson-Randall. 1999. Modeling the effects of nutria ( Myocastor coypus ) on wetland loss. Wetlands 19(1):209-219.

Keywords: nutria / Myocastor coypus / wetland loss / habitat conversion / Scirpus americanus /
Spartina patens / population dynamics / Louisiana / habitat loss / meso mammals / meso-mammals
48. Johnson, B. K., J. W. Kern, M. J. Wisdom, S. L. Finholt, and J. G. Kie. 2000. Resource selection and spatial separation of mule deer and elk during spring. J. Wildl. Manage. 64(3):685-697.
64, no. 3: 685-97.
Keywords: elk / Cervus elaphus / mule deer / Odocoileus hemionus / resource selection / resource selection functions / resource selection models / models / modeling / Starkey Project / telemetry /
Oregon / habitat use / movements / spatial distribution / spatial relationships
49. Johnson, D. E., ed. 1998. Special issue: resource selection using data from Geographic Information Systems
(GIS). Journal of Agricultural, Biological, and Environmental Statistics 3, no. 3: 237-345.
Keywords: statistics / methods / techniques / resource selection / habitat use / habitat selection / habitat preference / habitat availability / compositional analysis / chi-square analysis / logistic regression / models / modeling / resource selection functions
50. Jones, M. D., G. S. Warburton, and M. R. Pelton. 1995. Statistical models for predicting occupied black bear habitat in coastal North Carolina. Inter. Conf. Bear Res. and Manage. 10:in Press.
Keywords: black bears / Ursus americanus / habitat use / North Carolina / models / modeling / habitat occupancy / presence / distribution / agriculture / forests
51. Karl, J. W., N. M. Wright, P. J. Heglund, and J. M. Scott. 1999. Obtaining environmental measures to facilitate vertebrate habitat modeling. Wildl. Soc. Bull. 27(2):357-365.
Keywords: wildlife habitat modeling / GIS / habitat / literature search / forest structure / forest composition / topography / abiotic variables / habitat variables / soils / temperature / methods / techniques
52. Keating, K. A., and S. Cherry. 2004. Use and interpretation of logistic regression in habitat-selection studies.
J. Wildl. Manage.
68, no. 4: 774-89.
Keywords: logistic regression / models / modeling / resource selection functions / sampling design / habitat use / habitat availability / use-availability / statistics / methods / techniques / interpretation / exponential modeling / habitat modeling / log-binomialmodel / selection probability
53. Kilgo, J. C., D. L. Gartner, B. R. Chapman, J. B. Dunning, Jr., K. E. Franzreb, S. A. Gauthreaux, C. H.
Greenberg, D. J. Levey, K. V. Miller, and S. F. Pearson. 2002. A test of an expert-based bird-habitat relationship model in South Carolina. Wildl. Soc. Bull.
30, no. 3: 783-93.
Keywords: breeding birds / nongame birds / habitat-relationship model / habitat-relation model / models / modeling / accuracy / validation / Savannah River Site / South Carolina / species-habitat matrix / wildlife-habitat relationships / habitat use / GIS / Geographic Information Systems
54. Klaus, N. A., D. A. Buehler, and A. M. Saxton. 2005. Forest management alternatives and songbird breeding habitat on the Cherokee National Forest, Tennessee. J. Wildl. Manage.
69, no. 1: 222-34.
Keywords: Cherokee National Forest / Tennessee / songbirds / nongame birds / breeding birds / models / modeling / population viability / timber harvest / succession / natural disturbance / simulation / wildlife habitat suitability models
55. Knick, S. T., and J. T. Rotenberry. 1998. Limitations to mapping habitat use areas in changing landscapes using the Mahalanobis distance statistic. Journal of Agricultural, Biological, and Environmental
Statistics 3, no. 3: 311-22.
Keywords: statistics / methods / techniques / resource selection / habitat use / habitat selection / habitat preference / habitat availability / GIS / Geographical Information Systems / models / modeling / resource selection functions / Mahalanobis distance statistic / black-tailed jackrabbit /
Lepus californicus / shrubsteppe
56. Krohn, W. B. 1992. Sequence of habitat occupancy and abandonment: potential standards for testing habitat models. Wildl. Soc. Bull. 20(4):441-444.

Keywords: modeling / models / habitat models / Habitat Suitability Index models / HSI models / testing / validation / habitat occupancy / habitat abandonment
57. Kroll, A. J. , and J. B. Haufler. 2006. Development and evaluation of habitat models at multiple spatial scales:
A case study with the dusky flycatcher. Forest Ecology and Management 229, no. 2006: 161-69.
Keywords: breeding birds / songbirds / nongame birds / dusky flycatcher / Empidonax oberholseri /
Habitat Suitability Index models / HSI models / reproductive success / habitat occupancy / models / modeling / methods / techniques / understory vegetation / understory cover / canopy cover / forest structure / shrub cover / model testing / validation / model validation
58. Lancia, R. A., D. A. Adams, and E. M. Lunk. 1986. Temporal and spatial aspects of species-habitat models.
Pages 65-69 in J. Verner, M. L. Morrison, and C. J. Ralph, Eds. Wildlife 2000: Modeling Habitat
Relationships of Terrestrial Vertebrates. Univ. Wisconsin Press.
Keywords: models / modeling / modelling / species-habitat models / habitat use / habitat quality /
Habitat Suitability Index models / HSI models / methods / techniques
59. Larson, M. A., F. R. Thompson, III, J. J. Millspaugh, W. D. Dijak, and S. R. Shifley. 2004. Linking population viability, habitat suitability, and landscape simulation models for conservation planning.
Ecological Modelling 180, no. 2004: 103-18.
Keywords: population viability analysis / population viability models / HSI / habitat suitability index models / HSI models / landscape simulation / conservation planning / methods / techniques /
Missouri / GIS / landscape planning / LANDIS / RAMAS / simulation / ovenbirds / Seiurus aurocapillus / habitat modeling
60. Li, H., D. I. Gartner, P. Mou, and C. C. Trettin. 2000. A landscape model (LEEMATH) to evaluate effects of management impacts on timber and wildlife habitat. Computers and Electronics in Agriculture
27(2000):263-292.
Keywords: LEEMATH / South Carolina Landscape Study / wildlife habitat models / wildlife habitat modeling / models / modeling / forest management / decision-support systems / harvest scheduling / landscape planning / forest planning
61. Livingston, S. A., C. S. Todd, W. B. Krohn, and R. B. Owen, Jr. 1990. Habitat models for nesting bald eagles in Maine. J. Wildl. Manage. 54(4):644-653.
Keywords: bald eagles / Haliaeetus leucocephalus / Maine / habitat models / habitat modelling / habitat modeling / models / modeling / modelling / nest sites
62. Loehle, C., P. Van Deusen, T. B. Wigley, M. S. Mitchell, S. Rutzmoser, J. Aggett, J. A. Beebe, and M. L.
Smith. 2006. A method for landscape analysis of forestry guideliknes using bird habitat models and the Habplan harvest scheduler. Forest Ecology and Management 232 , no. 2006: 56-57.
Keywords: managed forests / landscape structure / bird species richness / Arkansas / South Carolina
/ West Virginia / forest structure / landscape heterogeneity / forest management / breeding birds / nongame birds / songbirds / harvest scheduler / harvest scheduling / Habplan / extended rotations / riparian forests / riparian zones / Sustainable Forestry Initiative / SFI
63. Loukmas, J. J., and R. S. Halbrook. 2001. A test of the mink habitat suitability index model for riverine systems. Wildl. Soc. Bull.
29, no. 3: 821-26.
Keywords: mink / minks / Mustela vison / Habitat Suitability Index models / HSI models / validation
/ Wisconsin / Great Lakes / methods / techniques / habitat use / bioindicators / habitat suitability / habitat use / activity / track boards
64. MacCracken, J. G., V. V. Ballenberghe, and J. M. Peek. 1997. Habitat relationships of moose on the Copper
River Delta in coastal south-central Alaska. Wildl. Monogr. 136:1-52.
Keywords: moose / Alces alces / activity / Alaska / carrying capacity / models / modeling / disturbance / habitat use / habitat selection

65. MacKenzie, D. I. 2006. Modeling the probability of resource use: The effect of, and dealing with, detecting a species imperfectly. Journal of Wildlife Management 70, no. 2: 367-74.
Keywords: resource selection / resource selection functions / logistic regression / Bayesian statistics
/ habitat use / statistics / methods / techniques / availability / food selection / preference / weighted distributions / compositional analysis / chi-square tests / use versus availability / risk assessment / discrete choice analysis / habitat modeling / occupancy modeling / absence / presence / detectability
66. MacKenzie, D. I. 2005. What are the issues with presence-absence data for wildlife managers? J. Wildl.
Manage.
69, no. 3: 849-60.
Keywords: presence-absence information / presence / absence / site occupancy / modeling / models / detection / detection probability / methods / techniques / habitat use / resource selection functions / species distribution / species range / occurrence / habitat modeling / statistics / statistical analysis
67. Manley, P. N., M. D. Schlesinger, J. K. Roth, and B. Van Horne. 2005. A field-based evaluation of a presence-absence protocol for monitoring ecoregional-scale biodivversity. J. Wildl. Manage.
69, no.
3: 950-966.
Keywords: presence-absence information / presence / absence / site occupancy / modeling / models / detection / detection probability / methods / techniques / habitat use / resource selection functions / species distribution / species range / occurrence / habitat modeling / statistics / statistical analysis / biodiversity / biological diversity / National Forest System / Sierra Nevada / USDA Forest Service
68. McCracken, M. L., B. F. J. Manly, and M. Vander Heyden. 1998. The use of discrete-choice models for evaluating resource selection. Journal of Agricultural, Biological, and Environmental Statistics 3, no. 3: 268-79.
Keywords: statistics / methods / techniques / resource selection / habitat use / habitat selection / habitat preference / habitat availability / independence / logit models / multinomial logit models / discrete choice models / discrete-choice models / models / modeling / resource selection functions
69. McDonald, T. L., B. F. J. Manly, R. M. Nielson, and L. V. Diller. 2006. Discrete-choice modeling in wildlife studies exemplified by northern spotted owl nighttime habitat selection. Journal of Wildlife
Management 70, no. 2: 375-83.
Keywords: resource selection / resource selection functions / logistic regression / Bayesian statistics
/ habitat use / statistics / methods / techniques / availability / food selection / preference / weighted distributions / compositional analysis / chi-square tests / use versus availability / risk assessment / discrete choice analysis / habitat modeling / occupancy modeling / absence / presence / detectability
/ northern spotted owls / Strix occidentalis caurina / timber harvest / forest management / foraging / discrete-choice modeling / logistic regression / maximum likelihood / California
70. McDonald, T. L., and L. L. McDonald. 2003. A new ecological risk assessment procedure using resource selection models and geographic information systems. Wildl. Soc. Bull.
30, no. 4: 1015-21.
Keywords: resource selection functions / GIS / geographic information systems / habitat use / risk assessment / methods / techniques / northern spotted owls / Strix occidentalis caurina / threatened species / endangered species
71. Miller, D. A., B. D. Leopold, G. A. Hurst, and P. D. Gerard. 2000. Habitat selection models for eastern wild turkeys in central Mississippi. J. Wildl. Manage. 64(3):765-776.
Keywords: eastern wild turkeys / Meleagris gallopavo silvestris / Mississippi / habitat use / habitat models / logistic regression / landscape ecology
72. Millspaugh, J. J., R. M. Nelson, L. McDonald, J. M. Marzluff, R. A. Gitzen, C. D. Rittenhouse, M. W.
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Journal of Wildlife Management 70, no. 2: 384-95.
Keywords: resource selection / resource selection functions / logistic regression / Bayesian statistics
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/ kernel / Poisson regression / radio telemetry
73. Mitchell, M. S., R. A. Lancia, and J. A. Gerwin. 2001. Using landscape-level data to predict the distribution of birds on a managed forest: effects of scale. Ecol. Appl. 11, no. 6: 1692-708.
Keywords: models / modeling / landscape ecology / Geographic Information Systems / GIS / logistic regression / songbirds / nongame birds / breeding birds / South Carolina / scale / habitat use
74. Mitchell, M. S., and R. A. Powell. 2003. Response of black bears to forest management in the southern
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67, no. 4: 692-705.
Keywords: black bears / Ursus americanus / forest management / GIS / habitat suitability index model / HSI model / North Carolina / Pisgah National Forest / soft mast / early successional forest / overstory vegetation / understory vegetation / home range / indicator species / logging roads / clearcutting / even-aged management
75. Mitchell, M. S., S. H. Rutzmoser, T. B. Wigley, C. Loehle, J. A. Gerwin, P. D. Keyser, R. A. Lancia, R. W.
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Keywords: breeding birds / nongame birds / avian communities / species richness / species occurrence / landscape structure / landscape ecology / landscape configuration / landscape pattern /
Arkansas / West Virginia / South Carolina / heterogeneity / habitat use / logistic regression / models
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76. Mitchell, M. S., J. W. Zimmerman, and R. A. Powell. 2002. Test of a habitat suitability index for black bears in the southern Appalachians. Wildl. Soc. Bull.
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Keywords: black bears / Ursus americanus / large mammals / habitat-relationship model / habitatrelation model / models / modeling / North Carolina / species-habitat relationships / wildlife-habitat relationships / habitat use / HSI model / Habitat Suitability Index model / southern Appalachians /
Southern Appalachian Mountains / Pisgah Bear Sanctuary
77. Montopoli, G. J., and D. A. Anderson. 1991. A logistic model for the cumulative effects of human intervention on bald eagle habitat. J. Wildl. Manage. 55(2):290-293.
Keywords: bald eagles / Haliaeetus leucocephalus / human disturbance / disturbance / habitat use / habitat alteration / recreation / habitat selection
78. Moore, J. E. , and R. K. Swihart. 2005. Modeling patch occupancy by forest rodents: Incorporating detectability and spatial autocorrelation with hierarchically structured data. J. Wildl. Manage.
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Keywords: presence-absence information / presence / absence / site occupancy / modeling / models / detection / detection probability / methods / techniques / habitat use / resource selection functions / species distribution / species range / occurrence / habitat modeling / statistics / statistical analysis / rodents / small mammals / Indiana / spatial autocorrelation / hierarchical generalized linear models
79. Morrison, M. L., I. C. Timossi, and K. A. With. 1987. Development and testing of linear regression models predicting bird-habitat relationships. J. Wildl. Manage. 51(1):247-253.
Keywords: Habitat Evaluation Procedures / Habitat Suitability Index / habitat models / bird-habitat relationship / nongame birds / songbirds / habitat quality / habitat modeling / models / modeling
80. Nadeau, S., R. DeCararie, D. Lambert, and M. St-Georges. 1995. Nonlinear modeling of muskrat use of habitat. J. Wildl. Manage. 59(1):110-117.
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81. Nelson, M. D., and R. R. Buech. 1996. A test of 3 models of Kirtland's warbler habitat suitability. Wildl. Soc.
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Keywords: Kirtland's warbler / Dendroica kirtlandii / breeding birds / nongame birds / habitat suitability / habitat use / models / modeling / modelling / Michigan / jack pine / Pinus banksiana / even-aged management / canopy cover / stem density / fire / prescribed fire / prescribed burning
82. Nielsen, C. K., and A. Woolf. 2002. Habitat-relative abundance relationships for bobcats in southern Illinois.
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Keywords: bobcats / Lynx rufus / habitat relationship models / relative abundance / models / modeling / habitat models / multivariate distance statistics / telemetry / predators / Illinois
83. Niemuth, N. D. 2003. Identifying landscapes for greater prairie chicken translocation using habitat models and GIS: a case study. Wildl. Soc. Bull.
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Keywords: prairie chicken / Tympanuchus cupido / Tympanuchus cupido cupido / Tympanuchus cupido attwateri / Tympanuchus cupido pinnatus / heath hen / GIS / habitat use / translocation / GIS / geographic information systems / models / modeling / sharp-tailed grouse / landscape ecology / spatially explicit models / habitat suitability
84. O'Brien, C. S., S. S. Hervert J. J. Rosenstock, J. L. Bright, and S. R. Boe. 2005. Landscape-level models of potential habitat for Sonoran pronghorn. Wildlife Society Bulletin 33, no. 1: 24-34.
Keywords: Sonoran pronghorn / Antilocapra americana sonoriensis / CART analysis / Classification and Regression Tree analysis / habitat use / models / modeling / logistic regression / landscape-level
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85. O'Neil, L. J., and A. B. Carey. 1986. When habitats fail as predictors. Pages 207-208 in J. Verner, M. L.
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Keywords: modeling / modelling / habitat / relationships / relationship / multivariate models / statistics / multivariate statistics / methods / techniques
87. O'Neil, L. J., T. H. Roberts, J. S. Wakeley, and J. W. Teaford. 1988. A procedure to modify habitat suitability index models. Wildl. Soc. Bull. 16(1):33-36.
Keywords: habitat suitability index / models / modifying / suitability index models / habitat evaluation / Habitat Suitability Index / techniques / Habitat Evaluation Procedures / habitat evaluation procedures / methods
88. Odom, R. H., W. M. Ford, J. W. Edwards, C. W. Stihler, and J. M. Menzel. 2001. Developing a habitat model for the endangered Virginia northern flying squirrel ( Glaucomys sabrinus fuscus ) in the Allegheny
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Keywords: Virginia northern flying squirrel / Glaucomys sabrinus fuscus / Allegheny Mountains /
West Virginia / habitat use / models / modeling / habitat models / logistic regression / nest boxes / nest box surveys / digital elevation models / GIS / Geographic Information Systems
89. Olson, G. S. , R. G. Anthony, E. D. Forsman, S. H. Ackers, P. J. Loschl, J. A. Reid, K. M. Dugger, E. M.
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69, no. 3: 918-32.
Keywords: presence-absence information / presence / absence / site occupancy / modeling / models / detection / detection probability / methods / techniques / habitat use / resource selection functions / species distribution / species range / occurrence / habitat modeling / statistics / statistical analysis / northern spotted owls / Strix occidentalis caurina / barred owls / Strix varia / Pacific Northwest /
Oregon / H. J. Andrews Experimental Forest / Willamette National Forest / Coast Range
90. Olson, G. S. , E. M. Glenn, R. G. Anthony, E. D. Forsman, J. A. Reid, P. J. Loschl, and W. J. Ripple. 2004.
Modeling demographic performance of northern spotted owls relative to forest habitat in Oregon. J.
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Keywords: northern spotted owls / raptors Strix occidentalis caurina / demographics / reproductive success / population modeling / habitat fitness potential / modeling / models / Oregon / Coast Range
/ barred owls / Strix varia / competition / precipitation / rainfall / rain / forest age

91. Osko, T. J., M. N. Hiltz, R. J. Hudson, and S. M. Wasel. 2004. Moose habitat preferences in response to changing availability. J. Wildl. Manage.
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Keywords: moose / Alberta / Alces alces / habitat use / telemetry / radiotelemetry / habitat suitability
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92. Otis, D. L. 1998. Analysis of the influence of spatial pattern in habitat selection studies. Journal of
Agricultural, Biological, and Environmental Statistics 3, no. 3: 254-67.
Keywords: statistics / methods / techniques / resource selection / habitat use / habitat selection / habitat preference / habitat availability / spatial pattern / GIS / Geographic Information Systems / poisson regression / GLIM models / landscape configuration / landscape pattern
93. Pauley, G. R., J. M. Peek, and P. Zager. 1993. Predicting white-tailed deer habitat use in Northern Idaho. J.
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Keywords: white-tailed deer / Odocoileus virginianus / habitat use / modeling / predicting / Idaho / old-growth forest / aspect / topography / forest type / understory vegetation / shrubs / tree density / overstory vegetation / canopy cover / stand age
94. Pendleton, G. W., K. Titus, E. DeGayner, C. J. Flatten, and R. E. Lowell. 1998. Compositional analysis and
GIS for study of habitat selection by goshawks in southeast Alaska. Journal of Agricultural,
Biological, and Environmental Statistics 3, no. 3: 280-295.
Keywords: statistics / methods / techniques / resource selection / habitat use / habitat selection / habitat preference / habitat availability / GIS / Geographical Information Systems / compositional analysis / northern goshawks / Accipiter gentilis / Alaska / log-ratio compositional analysis / models
/ modeling / resource selection functions
95. Penhollow, M. E., and D. F. Stauffer. 2000. Large-scale habitat relationships of neotropical migratory birds in
Virginia. J. Wildl. Manage. 64(2):362-373.
Keywords: nongame birds / breeding birds / songbirds / neotropical migratory birds / habitat use / landscape configuration / landscape pattern / landscape structure / landscape ecology / FRAGSTATS
/ modeling / models / Virginia
96. Pereira, J. M. C., and R. M. Itami. 1991. GIS-based habitat modeling using logistic multiple regression: a study of the Mt. Graham red squirrel. Photogrammetric Engineering & Remote Sensing
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Keywords: habitat use / models / modeling / GIS / Geographic Information Systems / spatial data / spatial analysis / Mt. Graham red squirrels / small mammals / Arizona / methods / techniques / logistic regression
97. Prather, J. W., N. L. Dodd, B. G. Dickson, H. M. Hampton, Y. Xu, E. N. Aumack, and T. D. Sisk. 2006.
Landscape models to predict the influence of forest structure on tassel-eared squirrel populations.
Journal of Wildlife Management 70, no. 3: 723-31.
Keywords: tassel-eared squirrel / Sciurus aberti / Southwest / Arizona / habitat use / models / modeling / forest structure / population density / AIC / Akaike's Information Criterion
98. Pulliam, H. R., J. Liu, J. B. Dunning, Jr., D. J. Stewart, and T. D. Bishop. 1994. Modelling animal populations in changing landscapes. Ibis 137:S120-S126
Keywords: Bachman's sparrow / Aimophila aestivalis / habitat use / forest management /
ECOLECON / modelling / modeling / spatially-explicit models / population dynamics / population models / rotation length / even-aged management / landscape structure / landscape models / landscape configuration / habitat area / stand size / forest age / fragmentation / juxtaposition / redcockaded woodpecker / Picoides borealis
99. Raedeke, K. J., and J. F. Lehmkuhl. 1986. A simulation procedure for modeling the relationships between wildlife and forest management. Pages 377-381 in J. Verner, M. L. Morrison, and C. J. Ralph, Eds.
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Keywords: modeling / modelling / habitat / relationships / relationship / succession / forest succession / forest structure / structure / HABSIM / models / model / silviculture / forest management / National Forests / forest planning
100. Raxworthy, C. J., E. Martinez-Meyer, N. Horning, R. A. Nussbaum, G. E. Schneider, M. A. Ortega-Huerta, and A. T. Peterson. 2003. Predicting distributions of known and unknown reptile species in
Madagascar. Nature 426, no. 18/25 December: 837-41.
Keywords: ecological niche models / ecological niche distribution models / GARP / Genetic
Algorithm for Rule-set Production / Genetic Algorithm Rule-set Production / Genetic Algorithm for
Rule Set Prediction / Genetic Algorithm for Rule Set Production / GARP Modeling System / GARP
Modelling System / methods / techniques / GIS / Geographic Information Systems / modeling / habitat use / habitat relationships / reptiles / Madagascar / models / modelling
101. Riffell, S. , T. Burton, and M. Murphy. 2006. Birds in depressional forest wetlands: Area and habitat requirements and model uncertainty. Wetlands 26, no. 1: 107-18.
Keywords: songbirds / nongame birds / breeding birds / depressional wetlands / isolated wetlands / vernal pools / Michigan / species-area relationship / forested wetlands / Kullback-Leiber information
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102. Riitters, K. H., R. V. O'Neill, and K. B. Jones. 1997. Assessing habitat suitability at multiple scales: A landscape-level approach. Biol. Conserv.
81, no. 1997: 191-202.
Keywords: landscape ecology / landscape metrics / fragmentation / FRAGSTATS / spatial statistics / risk assessment / scale / wildlife habitat models / habitat suitability models / Chesapeake Bay
Watershed / landscape pattern / landscape configuration
103. Robel, R. J., L. B. Fox, and K. E. Kemp. 1993. Relationship between habitat suitability index values and ground counts of beaver colonies in Kansas. Wildl. Soc. Bull. 21(4):415-421.
Keywords: beavers / Castor canadensis / density / population density / abundance / density / habitat use / habitat suitability index models / HSI models / Kansas
104. Roloff, G. J., and B. J. Kernohan. 1999. Evaluating reliability of habitat suitability index models. Wildl. Soc.
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Keywords: Habitat Suitability Index models / HSI models / testing / evaluation / validation / habitat models / methods / techniques
105. Roloff, G. J., J. J. Millspaugh, R. A. Gitzen, and G. C. Brundige. 2001. Validation tests of a spatially explicit habitat effectiveness model for Rocky Mountain elk. J. Wildl. Manage.
65, no. 4: 899-914.
Keywords: Rocky Mountain elk / Cervus elaphus / models / modeling / validation / elk / South
Dakota / habitat use / Volume of Intersection / habitat effectiveness / telemetry
106. Roseberry, J. L., and Q. Hao. 1996. Interactive computer program for landscape-level habitat analysis. Wildl.
Soc. Bull. 24(2):340-341.
Keywords: computer software / landscape ecology / landscape metrics / models / modeling / HAMS
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107. Roseberry, J. L., and S. C. Sudkamp. 1998. Assessing the suitability of landscapes for northern bobwhite. J.
Wildl. Manage. 62(3):895-902.
Keywords: northern bobwhites / Colinus virginianus / habitat modeling / Illinois / landscape ecology
/ PATREC / Pattern Recognition Models / FRAGSTATS / models / modeling / Breeding Bird
Survey / landscape configuration / landscape structure / row crops / edges / fragmentation / contagion / grasslands
108. Rowland, M. M., M. J. Wisdom, B. K. Johnson, and J. G. Kie. 2000. Elk distribution and modeling in relation to roads. J. Wildl. Manage. 64(3):672-684.

Keywords: elk / Cervus elaphus / forest management / road density / models / modeling / Starkey
Project / telemetry / access / Oregon / habitat use / roads / movements
109. Rowland, M. M., M. J. Wisdom, D. H. Johnson, B. C. Wales, J. P. Copeland, and F. B. Edelmann. 2003.
Evaluation of landscape models for wolverines in the interior Northwest, United States of America.
J. Mammal.
84, no. 1: 92-105.
Keywords: wolverines / Gulo gulo / large mammals / carnivores / forest carnivores / Interior
Northwest / Pacific Northwest / Oregon / Washington, Idaho / Montana / road density / human population density / suitable habitat / habitat suitability / models / modeling / landscape ecology / watershed models / subbasin models / Bayesian models / Columbia basin
110. Schroeder, R. L., T. T. Cable, and S. L. Haire. 1992. Wildlife species richness in shelterbelts: test of a habitat model. Wildl. Soc. Bull. 20(3):264-273.
Keywords: shelterbelts / corridors / streamside management zones / HSI models / Habitat Suitability
Index models / HEP / foliage height diversity / birds / breeding birds / nongame birds / songbirds / habitat evaluation
111. Schroeder, R. L., and L. D. Vangilder. 1997. Tests of wildlife habitat models to evaluate oak-mast production. Wildl. Soc. Bull. 25(3):639-646.
Keywords: oak mast / mast / oaks / Quercus spp. / acorns / acorn production / mast production / wildlife habitat models / HSI models / Habitat Suitability Index models / tree density / canopy cover
/ canopy closure
112. Schulz, T. T., and L. A. Joyce. 1992. A spatial application of a marten habitat model. Wildl. Soc. Bull.
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Keywords: marten / Martes americana / pine marten / habitat model / landscape ecology / grain size / landscape / forest management / dominance / contagion / diversity
113. Shifley, S. R., F. R. Thompson, III, W. D. Dijak, M. A. Larson, and J. J. Millspaugh. 2006. Simulated effects of forest management alternatives on landscape structure and habitat suitability in the midwestern
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Keywords: coarse woody debris / down woody debris / Habitat Suitability Index models / HSI models / timber harvest / disturbance / fire / oak-hickory forests / Ozark Mountains / Ozark
Highlands / LANDIS / simulation / modeling / models / Missouri / ovenbird / Seiurus aurocapilla / prairie warbler / Dendroica discolor / hooded warblers / Wilsonia citrina / gray squirrel / Sciurus carolinensis / small mammals / songbirds / breeding birds / nongame birds / forest management
114. Smith, K. G., and P. G. Connors. 1986. Building predictive models of species occurrence from total-count transect data and habitat measurements. Pages 45-50 in J. Verner, M. L. Morrison, and C. J. Ralph,
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Keywords: modeling / modelling / habitat / relationships / relationship / birds / wading birds / waterbirds / logistic regression / functional analysis of categorical data / methods / techniques / statistics / FUNCAT / nongame birds
115. Smith, T. M., H. H. Shugart, and D. C. West. 1981. Use of forest simulation models to integrate timber harvest and nongame bird management. Trans. N. Amer. Wildl. and Natur. Conf. 46:501-510.
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116. Stanley, T. R., and J. A. Royle. 2005. Estimating site occupancy and abundance using indirect detection indices. J. Wildl. Manage.
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Keywords: presence-absence information / presence / absence / site occupancy / modeling / models / detection / detection probability / methods / techniques / habitat use / resource selection functions / species distribution / species range / occurrence / habitat modeling / statistics / statistical analysis / indirect detection indices / detection indices / population estimation / small mammals / scent stations

/ tracking tubes
117. Stauffer, D. F., G. A. Cline, and M. J. Tonkovich. 1990. Evaluating potential effects of CRP on bobwhite quail in Piedmont Virginia. Trans. N. Amer. Wildl. and Natur. Conf. 55:57-67.
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118. Stockwell, D., and D. Peters. 1999. The GARP modelling system: problems and solutions to automated spatial prediction. Int. J. Geographical Information Science 13, no. 2: 143-58.
Keywords: GARP / Genetic Algorithm for Rule-set Production / Genetic Algorithm Rule-set
Production / Genetic Algorithm for Rule Set Prediction / Genetic Algorithm for Rule Set Production
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Information Systems / modeling / habitat use / habitat relationships
119. Stoms, D. M., F. W. Davis, and C. B. Cogan. 1992. Sensitivity of wildlife habitat models to uncertainties in
GIS data. Photogrammetric Engineering and Remote Sensing 58(6):843-850. 58, no. 6: 843-50.
Keywords: remote sensing / Geographic Information Systems / GIS / sensitivity analysis / reliability
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120. Tallman, R. E. 2001. Habitat characteristics of the cerulean warbler (Dendroica cerulea) in West Virginia: development of a predictive model. M. S. Thesis, Fostburg State University, Frostburg, MD. 65pp.
Keywords: cerulean warblers / Dendroica cerulea / models / modeling / habitat use / habitat relationship models / West Virginia / discriminant analysis / discriminant function analysis / canopy cover / forest structure
121. Temple, S. A. 1986. Predicting impacts of habitat fragmentation on forest birds: a comparison of two models.
Pages 301-304 in J. Verner, M. L. Morrison, and C. J. Ralph, Eds. Wildlife 2000, Modeling Habitat
Relationships of Terrestrial Vertebrates. Univ. Wisconsin Press.
Keywords: modeling / modelling / habitat / relationships / relationship / birds / breeding birds / songbirds / Europe / fragmentation / forest fragmentation / islands
122. Temple, S. A., and J. R. Cary. 1988. Modeling dynamics of habitat-interior bird populations in fragmented landscapes. Conserv. Biol. 2(4):340-347.
Keywords: birds / nongame birds / habitat-interior species / forest-interior species / fragmentation / modeling / edges / fecundity / immigration / reproductive success
123. Thatcher, C. A., F. T. Van Manen, and J. D. Clark. 2006. Identifying suitable sites for Florida panther reintroduction. Journal of Wildlife Management 70, no. 3: 752-63.
Keywords: Florida panthers / Puma concolor / Southeast / Florida / reintroduction / telemetry / translocation / habitat use / models / modeling / habitat models / GIS / Mahalanobis distance / habitat modeling
124. Thomas, D. L., D. Johnson, and B. Griffith. 2006. A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference. Journal of Wildlife Management 70, no. 2:
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Keywords: resource selection / resource selection functions / logistic regression / Bayesian statistics
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125. Thomasma, L. E., T. D. Drummer, and R. O. Peterson. 1991. Testing the habitat suitability index model for the fisher. Wildl. Soc. Bull. 19, no. 3: 291-97.
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126. Thompson, F. R., III, J. D. Brawn, S. Robinson, J. Faaborg, and R. L. Clawson. 2000. Approaches to investigate effects of forest management on birds in eastern deciduous forests: How reliable is our knowledge? Wildl. Soc. Bull. 28, no. 4: 1111-22.
Keywords: breeding birds / winter birds / birds / songbirds / neotropical migratory birds / forest management / habitat use / forest structure / landscape ecology / fragmentation / landscape pattern / clearcutting / even-aged management / nesting success / productiity / reroductive success / edge effects / predation / brood parasitism / cowbirds / Molothrus ater / study design / experimental design / methods / techniques / review / eastern deciduous forests / models / modeling
127. Thompson, I. D., J. A. Baker, and M. Ter-Mikaelian. 2003. A review of the long-term effects of post-harvest silviculture on vertebrate wildlife, and predictive models, with an emphasis on boreal forests in
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177, no. 2003: 441-69.
Keywords: intensive forest management / silviculture / large mammals / small mammals / amphiians
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128. Van Deusen, P. C. 1996. Habitat and harvest scheduling using Bayesian statistical concepts. Can. J. For. Res.
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129. Van Horne, B., and J. A. Wiens. 1991. Forest bird habitat suitability models and the development of general habitat models. U.S. Fish and Wildl. Serv., Fish Wildl. Res. 8. 31pp. 8: 1-31.
Keywords: forest birds / breeding birds / winter birds / songbirds / nongame birds / models / habitat suitability index models / habitat suitability models / HSI / Habitat Suitability Index / habitat use / modeling / methods / techniques / modelling
130. van Manen, F. T., and M. R. Pelton. 1997. A GIS model to predict black bear habitat use. J. For. 95, no. 8: 6-
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131. Vojta, C. D. 2005. Old dog, new tricks: Innovations with presence-absence information. J. Wildl. Manage.
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Keywords: presence-absence information / presence / absence / site occupancy / modeling / models / detection / detection probability / methods / techniques / habitat use / resource selection functions / species distribution / species range / occurrence / habitat modeling / statistics / statistical analysis
132. Welsh, H. H., Jr., J. R. Dunk, and W. J. Zielinski. 2006. Developing and applying habitat models using forest inventory data: An example using a terrestrial salamander. Journal of Wildlife Management 70, no.
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Keywords: salamanders / herpetofauna / terrestrial salamanders / Del Norte salamander / Plethodon elongatus / Akaike's Information Criterion / AIC / forest inventory / Forest Inventory and Analysis /
FIA / Pacific Northwest / amphibians / models / modeling / habitat use / wildlife habitat models /
California