Tools and Techniques for Monitoring Wildlife Habitats, Communities, and Populations
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By Forest and Rangeland Ecosystem Science Center
November 14, 2017
Resource monitoring is critically important for documenting trends and learning from the past (i.e., adaptive management), yet it has been plagued with poor design and execution. We are developing and testing novel approaches to wildlife monitoring, including the use of non-invasive field sampling and molecular markers to determine patterns of species occurrence and population abundance relative to management actions or habitat conditions. We are using remote sensing methods to improve mapping and prediction of wildlife habitats and the quality of those habitats for different species.
Below are other science projects associated with this project.
Below are publications associated with this project.
Filter Total Items: 32
Appropriate sample sizes for monitoring burned pastures in sagebrush steppe: How many plots are enough, and can one size fit all? Appropriate sample sizes for monitoring burned pastures in sagebrush steppe: How many plots are enough, and can one size fit all?
Statistically defensible information on vegetation conditions is needed to guide rangeland management decisions following disturbances such as wildfire, often for heterogeneous pastures. Here we evaluate the number of plots needed to make informed adaptive management decisions using >2000 plots sampled on the 2015 Soda Fire that burned across 75 pastures and 113,000 ha in Idaho and...
Authors
Cara Applestein, Matthew J. Germino, David S. Pilliod, Matthew Fisk, Robert S. Arkle
Quantifying climate sensitivity and climate-driven change in North American amphibian communities Quantifying climate sensitivity and climate-driven change in North American amphibian communities
Changing climate will impact species’ ranges only when environmental variability directly impacts the demography of local populations. However, measurement of demographic responses to climate change has largely been limited to single species and locations. Here we show that amphibian communities are responsive to climatic variability, using >500,000 time-series observations for 81...
Authors
David A.W. Miller, Evan H. Campbell Grant, Erin L. Muths, Staci M. Amburgey, M. J. Adams, Maxwell B. Joseph, J. Hardin Waddle, Pieter T.J. Johnson, Maureen E. Ryan, Benedikt R. Schmidt, Daniel L. Calhoun, Courtney L. Davis, Robert N. Fisher, David M. Green, Blake R. Hossack, Tracy A.G. Rittenhouse, Susan C. Walls, Larissa L. Bailey, Sam S. Cruickshank, Gary M. Fellers, Thomas A. Gorman, Carola A. Haas, Ward Hughson, David S. Pilliod, Steven J. Price, Andrew M. Ray, Walter Sadinski, Daniel Saenz, William J. Barichivich, Adrianne B. Brand, Cheryl S. Brehme, Rosi Dagit, Katy S. Delaney, Brad M. Glorioso, Lee B. Kats, Patrick M. Kleeman, Christopher Pearl, Carlton J. Rochester, Seth P. D. Riley, Mark F. Roth, Brent Sigafus
By
Ecosystems Mission Area, Water Resources Mission Area, Species Management Research Program, Eastern Ecological Science Center, Forest and Rangeland Ecosystem Science Center, Fort Collins Science Center, John Wesley Powell Center for Analysis and Synthesis, Northern Rocky Mountain Science Center, South Atlantic Water Science Center (SAWSC), Southwest Biological Science Center, Upper Midwest Environmental Sciences Center, Western Ecological Research Center (WERC), Wetland and Aquatic Research Center
An introduction and practical guide to use of the Soil-Vegetation Inventory Method (SVIM) data An introduction and practical guide to use of the Soil-Vegetation Inventory Method (SVIM) data
Long-term vegetation dynamics across public rangelands in the western United States are not well understood because of the lack of large-scale, readily available historic datasets. The Bureau of Land Management’s Soil-Vegetation Inventory Method (SVIM) program was implemented between 1977 and 1983 across 14 western states, but the data have not been easily accessible. We introduce the...
Authors
Brittany S. Barker, David S. Pilliod, Justin L. Welty, Robert S. Arkle, Michael G. Karl, Gordon Toevs
An analytical framework for estimating aquatic species density from environmental DNA An analytical framework for estimating aquatic species density from environmental DNA
Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon...
Authors
Thierry Chambert, David S. Pilliod, Caren S. Goldberg, Hideyuki Doi, Teruhiko Takahara
Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe
Terrestrial laser scanning (TLS) provides fast collection of high-definition structural information, making it a valuable field instrument to many monitoring applications. A weakness of TLS collections, especially in vegetation, is the occurrence of unsampled regions in point clouds where the sensor’s line-of-sight is blocked by intervening material. This problem, referred to as...
Authors
Kyle E. Anderson, Nancy Glenn, Lucas Spaete, Douglas J. Shinneman, David S. Pilliod, Robert Arkle, Susan McIlroy, DeWayne R. Derryberry
Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales
Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m...
Authors
Aihua Li, Shital Dhakal, Nancy F. Glenn, Luke P. Spaete, Douglas J. Shinneman, David S. Pilliod, Robert Arkle, Susan McIlroy
Resource monitoring is critically important for documenting trends and learning from the past (i.e., adaptive management), yet it has been plagued with poor design and execution. We are developing and testing novel approaches to wildlife monitoring, including the use of non-invasive field sampling and molecular markers to determine patterns of species occurrence and population abundance relative to management actions or habitat conditions. We are using remote sensing methods to improve mapping and prediction of wildlife habitats and the quality of those habitats for different species.
Below are other science projects associated with this project.
Below are publications associated with this project.
Filter Total Items: 32
Appropriate sample sizes for monitoring burned pastures in sagebrush steppe: How many plots are enough, and can one size fit all? Appropriate sample sizes for monitoring burned pastures in sagebrush steppe: How many plots are enough, and can one size fit all?
Statistically defensible information on vegetation conditions is needed to guide rangeland management decisions following disturbances such as wildfire, often for heterogeneous pastures. Here we evaluate the number of plots needed to make informed adaptive management decisions using >2000 plots sampled on the 2015 Soda Fire that burned across 75 pastures and 113,000 ha in Idaho and...
Authors
Cara Applestein, Matthew J. Germino, David S. Pilliod, Matthew Fisk, Robert S. Arkle
Quantifying climate sensitivity and climate-driven change in North American amphibian communities Quantifying climate sensitivity and climate-driven change in North American amphibian communities
Changing climate will impact species’ ranges only when environmental variability directly impacts the demography of local populations. However, measurement of demographic responses to climate change has largely been limited to single species and locations. Here we show that amphibian communities are responsive to climatic variability, using >500,000 time-series observations for 81...
Authors
David A.W. Miller, Evan H. Campbell Grant, Erin L. Muths, Staci M. Amburgey, M. J. Adams, Maxwell B. Joseph, J. Hardin Waddle, Pieter T.J. Johnson, Maureen E. Ryan, Benedikt R. Schmidt, Daniel L. Calhoun, Courtney L. Davis, Robert N. Fisher, David M. Green, Blake R. Hossack, Tracy A.G. Rittenhouse, Susan C. Walls, Larissa L. Bailey, Sam S. Cruickshank, Gary M. Fellers, Thomas A. Gorman, Carola A. Haas, Ward Hughson, David S. Pilliod, Steven J. Price, Andrew M. Ray, Walter Sadinski, Daniel Saenz, William J. Barichivich, Adrianne B. Brand, Cheryl S. Brehme, Rosi Dagit, Katy S. Delaney, Brad M. Glorioso, Lee B. Kats, Patrick M. Kleeman, Christopher Pearl, Carlton J. Rochester, Seth P. D. Riley, Mark F. Roth, Brent Sigafus
By
Ecosystems Mission Area, Water Resources Mission Area, Species Management Research Program, Eastern Ecological Science Center, Forest and Rangeland Ecosystem Science Center, Fort Collins Science Center, John Wesley Powell Center for Analysis and Synthesis, Northern Rocky Mountain Science Center, South Atlantic Water Science Center (SAWSC), Southwest Biological Science Center, Upper Midwest Environmental Sciences Center, Western Ecological Research Center (WERC), Wetland and Aquatic Research Center
An introduction and practical guide to use of the Soil-Vegetation Inventory Method (SVIM) data An introduction and practical guide to use of the Soil-Vegetation Inventory Method (SVIM) data
Long-term vegetation dynamics across public rangelands in the western United States are not well understood because of the lack of large-scale, readily available historic datasets. The Bureau of Land Management’s Soil-Vegetation Inventory Method (SVIM) program was implemented between 1977 and 1983 across 14 western states, but the data have not been easily accessible. We introduce the...
Authors
Brittany S. Barker, David S. Pilliod, Justin L. Welty, Robert S. Arkle, Michael G. Karl, Gordon Toevs
An analytical framework for estimating aquatic species density from environmental DNA An analytical framework for estimating aquatic species density from environmental DNA
Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon...
Authors
Thierry Chambert, David S. Pilliod, Caren S. Goldberg, Hideyuki Doi, Teruhiko Takahara
Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe
Terrestrial laser scanning (TLS) provides fast collection of high-definition structural information, making it a valuable field instrument to many monitoring applications. A weakness of TLS collections, especially in vegetation, is the occurrence of unsampled regions in point clouds where the sensor’s line-of-sight is blocked by intervening material. This problem, referred to as...
Authors
Kyle E. Anderson, Nancy Glenn, Lucas Spaete, Douglas J. Shinneman, David S. Pilliod, Robert Arkle, Susan McIlroy, DeWayne R. Derryberry
Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales
Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m...
Authors
Aihua Li, Shital Dhakal, Nancy F. Glenn, Luke P. Spaete, Douglas J. Shinneman, David S. Pilliod, Robert Arkle, Susan McIlroy