Predicting forest understory habitat for Canada lynx using LIDAR data
ABSTRACT Canada lynx (Lynx canadensis) is a federally threatened species in the contiguous United States. Within National Forests covered by the Northern Rockies Lynx Management Direction, Federal land managers must consider the effect of management activities on Canada lynx habitat. A common method...
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| Format: | Article |
| Language: | English |
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Wiley
2019-12-01
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| Series: | Wildlife Society Bulletin |
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| Online Access: | https://doi.org/10.1002/wsb.1018 |
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| author | Patrick A. Fekety Rema B. Sadak Joel D. Sauder Andrew T. Hudak Michael J. Falkowski |
| author_facet | Patrick A. Fekety Rema B. Sadak Joel D. Sauder Andrew T. Hudak Michael J. Falkowski |
| author_sort | Patrick A. Fekety |
| collection | DOAJ |
| description | ABSTRACT Canada lynx (Lynx canadensis) is a federally threatened species in the contiguous United States. Within National Forests covered by the Northern Rockies Lynx Management Direction, Federal land managers must consider the effect of management activities on Canada lynx habitat. A common method to assess Canada lynx habitat used by the U.S. Forest Service is to measure horizontal cover using a cover board. We used field measurements and airborne Light Detection and Ranging (LIDAR) metrics to test beta regression models that predict estimates of horizontal cover on the Nez Perce–Clearwater National Forest, Idaho, USA, 2009–2015. We also investigated the effect on model predictions when the cover board was blocked by the main stem of a tree. Model fit statistics for normalized root mean square errors (RMSE%) were 30.8–33.7% and pseudo‐R2 ranged from 0.64 to 0.71. Using independent validation data, model performance statistics for RMSE% were 24.6–33.5% and R2 ranged from 0.51 to 0.69. We found that removing cover board measurements where the main stem of a tree blocked >75% of the cover board produced the best model statistics. These models can be applied across LIDAR extents resulting in maps of horizontal cover estimates, which may be used in assessing effects of management activities on Canada lynx habitat. © 2019 The Wildlife Society. |
| format | Article |
| id | doaj-art-642cc87de12e4e319307187a9cd554ed |
| institution | OA Journals |
| issn | 2328-5540 |
| language | English |
| publishDate | 2019-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Wildlife Society Bulletin |
| spelling | doaj-art-642cc87de12e4e319307187a9cd554ed2025-08-20T01:57:49ZengWileyWildlife Society Bulletin2328-55402019-12-0143461962910.1002/wsb.1018Predicting forest understory habitat for Canada lynx using LIDAR dataPatrick A. Fekety0Rema B. Sadak1Joel D. Sauder2Andrew T. Hudak3Michael J. Falkowski4Department of Ecosystem Science & Sustainability Colorado State University Campus Delivery 1476 Fort Collins CO 80523 USAU.S. Department of Agriculture Forest Service Intermountain Region 324 25th Street Ogden UT 84401 USAIdaho Department of Fish and Game 3316 16th Street Lewiston ID 83501 USAU.S. Department of Agriculture Forest Service Rocky Mountain Research Station 1221 S Main Street Moscow ID 83843 USADepartment of Ecosystem Science & Sustainability Colorado State University Campus Delivery 1476 Fort Collins CO 80523 USAABSTRACT Canada lynx (Lynx canadensis) is a federally threatened species in the contiguous United States. Within National Forests covered by the Northern Rockies Lynx Management Direction, Federal land managers must consider the effect of management activities on Canada lynx habitat. A common method to assess Canada lynx habitat used by the U.S. Forest Service is to measure horizontal cover using a cover board. We used field measurements and airborne Light Detection and Ranging (LIDAR) metrics to test beta regression models that predict estimates of horizontal cover on the Nez Perce–Clearwater National Forest, Idaho, USA, 2009–2015. We also investigated the effect on model predictions when the cover board was blocked by the main stem of a tree. Model fit statistics for normalized root mean square errors (RMSE%) were 30.8–33.7% and pseudo‐R2 ranged from 0.64 to 0.71. Using independent validation data, model performance statistics for RMSE% were 24.6–33.5% and R2 ranged from 0.51 to 0.69. We found that removing cover board measurements where the main stem of a tree blocked >75% of the cover board produced the best model statistics. These models can be applied across LIDAR extents resulting in maps of horizontal cover estimates, which may be used in assessing effects of management activities on Canada lynx habitat. © 2019 The Wildlife Society.https://doi.org/10.1002/wsb.1018beta regressioncover boardhorizontal coverLynx canadensisNorthern Rocky Mountains |
| spellingShingle | Patrick A. Fekety Rema B. Sadak Joel D. Sauder Andrew T. Hudak Michael J. Falkowski Predicting forest understory habitat for Canada lynx using LIDAR data Wildlife Society Bulletin beta regression cover board horizontal cover Lynx canadensis Northern Rocky Mountains |
| title | Predicting forest understory habitat for Canada lynx using LIDAR data |
| title_full | Predicting forest understory habitat for Canada lynx using LIDAR data |
| title_fullStr | Predicting forest understory habitat for Canada lynx using LIDAR data |
| title_full_unstemmed | Predicting forest understory habitat for Canada lynx using LIDAR data |
| title_short | Predicting forest understory habitat for Canada lynx using LIDAR data |
| title_sort | predicting forest understory habitat for canada lynx using lidar data |
| topic | beta regression cover board horizontal cover Lynx canadensis Northern Rocky Mountains |
| url | https://doi.org/10.1002/wsb.1018 |
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