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  • Light Detection and Ranging-Based Measures of Mixed Hardwood Forest Structure | SILVIS Lab
    to LiDAR return heights We compared models using all LiDAR returns and only first returns First return univariate models explained more variability than all return models however the differences were small for multivariate models Multiple regression models had R2 values of 65 for sawtimber and pulpwood volume 63 for Lorey s mean tree height 55 for mean tree height 48 for mean dbh 46 for basal area and 13 for tree density However the standard error of the mean for predictions ranged between 1 and 4 and this level of error is well within levels needed for broad scale forest assessments Our results suggest that low density LiDAR intended for terrain mapping is valuable for broad scale hardwood forest inventories Hawbaker etal Lidar ForestScience 2010 pdf HOME PEOPLE Faculty Anna M Pidgeon Volker C Radeloff Staff David Helmers Nicholas Keuler Shelley Schmidt Post Docs Research Scientists Teri Allendorf Andrew Allstadt Brooke Bateman Eugenia Bragina Sebastian Martinuzzi Eric Wood Graduate Students Patricia Alexandre James Burnham Sarah Carter Diana Guzmán Colón Jessica Gorzo Chris Hamilton Max Henschell Catalina Munteanu Carlos Ramirez Reyes Isabel Rojas Viada Paul Schilke Naparat Suttidate Ana María Venegas Visiting Scientists Alumni Alexander Prishchepov Alexia Sabor Alexandra D Syphard

    Original URL path: http://silvis.forest.wisc.edu/publications/Light-Detection-and-Ranging-Based-Measures-Mixed-Hardwood-Forest-Structure (2015-03-07)
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  • Invasion of glossy privet (Ligustrum lucidum) and native forest loss in the Sierras Chicas of Cordoba, Argentina | SILVIS Lab
    stands and the changes in biodiversity and forest structure of the invaded areas The objectives of this paper were 1 to map the distribution of glossy privet stands in an area representative of the Sierras Chicas Co rdoba Argentina and 2 compare composition structure and regeneration between glossy privet invaded stands and native forest stands Using four Landsat TM images October 2005 March May and July 2006 we mapped the distribution of a glossy privet dominated stand using a support vector machine a non parametric classifier We recorded forest structure variables and tree diversity on 105 field plots Glossy privet dominated stands occupied 3 407 ha of the total forested land in the study area 27 758 ha had an average of 33 glossy privet trees dbh 2 5 cm per plot and the cover of their shrub and herb strata was substantially reduced compared with native forest Forest regeneration was dominated by glossy privet in native forest stands adjacent to glossy privet dominated stands We conclude that in the Sierras Chicas glossy privet has become a widespread invader changing the patterns of vertical structure diversity and regeneration in native forests Hoyos etal BiologicalInvasions2010 pdf HOME PEOPLE Faculty Anna M Pidgeon Volker C Radeloff Staff David Helmers Nicholas Keuler Shelley Schmidt Post Docs Research Scientists Teri Allendorf Andrew Allstadt Brooke Bateman Eugenia Bragina Sebastian Martinuzzi Eric Wood Graduate Students Patricia Alexandre James Burnham Sarah Carter Diana Guzmán Colón Jessica Gorzo Chris Hamilton Max Henschell Catalina Munteanu Carlos Ramirez Reyes Isabel Rojas Viada Paul Schilke Naparat Suttidate Ana María Venegas Visiting Scientists Alumni Alexander Prishchepov Alexia Sabor Alexandra D Syphard Anna Estes Adrian Lesak Avi Bar Massada Camilo Alcántara Chadwick Rittenhouse Charlotte Gonzalez Abraham Chunguang He David La Puma Elzbieta Laszczak Emily Duerr Frederic Beaudry Glen Aronson Gregory Gavier Pizarro Jodi

    Original URL path: http://silvis.forest.wisc.edu/publications/Invasion-glossy-privet-Ligustrum-lucidum-and-native-forest-loss-Sierras-Chicas-Cordoba (2015-03-07)
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  • Habitat variables explain Loggerhead Shrike occurrence in the northern Chihuahuan Desert, but are poor correlates of fitness measures | SILVIS Lab
    New Mexico to answer two questions 1 are highly used habitats of high quality for shrikes in terms of individual fitness and 2 what are the spatial scales of habitat associations relevant to this species Our study area was Fort Bliss Army Reserve New Mexico Bird abundance was obtained from 10 min point counts conducted at forty two 108 ha plots during a 3 year period Measures of fitness were obtained by tracking a total of 73 nests over the 3 years Habitat variables were measured at spatial scales ranging from broad to intermediate to local We related habitat use and measures of fitness to habitat variables using Bayesian model averaging We found a significant relationship between bird abundance and measures of fitness averaged across nesting birds in each plot correlation up to 0 61 This suggests that measures of habitat use are indicative of habitat quality in the vicinity of Fort Bliss Local and intermediate scale variables best explained shrike occurrence Habitat variables were not related to any measures of fitness A better understanding of the factors that limit individual bird fitness is therefore necessary to identify areas of high conservation value for this species StLouis etAl LandscapeEcology 2010 pdf HOME PEOPLE Faculty Anna M Pidgeon Volker C Radeloff Staff David Helmers Nicholas Keuler Shelley Schmidt Post Docs Research Scientists Teri Allendorf Andrew Allstadt Brooke Bateman Eugenia Bragina Sebastian Martinuzzi Eric Wood Graduate Students Patricia Alexandre James Burnham Sarah Carter Diana Guzmán Colón Jessica Gorzo Chris Hamilton Max Henschell Catalina Munteanu Carlos Ramirez Reyes Isabel Rojas Viada Paul Schilke Naparat Suttidate Ana María Venegas Visiting Scientists Alumni Alexander Prishchepov Alexia Sabor Alexandra D Syphard Anna Estes Adrian Lesak Avi Bar Massada Camilo Alcántara Chadwick Rittenhouse Charlotte Gonzalez Abraham Chunguang He David La Puma Elzbieta Laszczak Emily Duerr Frederic Beaudry

    Original URL path: http://silvis.forest.wisc.edu/publications/Habitat-variables-explain-Loggerhead-Shrike-occurrence-northern-Chihuahuan-Desert-are (2015-03-07)
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  • Remote sensing of vegetation 3-D structure for biodiversity and habitat: Review and implications for lidar and radar spaceborne missions | SILVIS Lab
    component of biodiversity and habitat has been until recently largely restricted to local measurements or at larger scales to generalizations New lidar and radar remote sensing instruments such as those proposed for spaceborne missions will provide the capability to fill this gap This paper reviews the state of the art for incorporating information on vegetation 3 D structure into biodiversity and habitat science and management approaches with emphasis on use of lidar and radar data First we review relationships between vegetation 3 D structure biodiversity and habitat and metrics commonly used to describe those relationships Next we review the technical capabilities of new lidar and radar sensors and their application to biodiversity and habitat studies to date We then define variables that have been identified as both useful and feasible to retrieve from spaceborne lidar and radar observations and provide their accuracy and precision requirements We conclude with a brief discussion of implications for spaceborne missions and research programs The possibility to derive vegetation 3 D measurements from spaceborne active sensors and to integrate them into science and management comes at a critical juncture for global biodiversity conservation and opens new possibilities for advanced scientific analysis of habitat and biodiversity Bergen etal JGR 2010 pdf HOME PEOPLE Faculty Anna M Pidgeon Volker C Radeloff Staff David Helmers Nicholas Keuler Shelley Schmidt Post Docs Research Scientists Teri Allendorf Andrew Allstadt Brooke Bateman Eugenia Bragina Sebastian Martinuzzi Eric Wood Graduate Students Patricia Alexandre James Burnham Sarah Carter Diana Guzmán Colón Jessica Gorzo Chris Hamilton Max Henschell Catalina Munteanu Carlos Ramirez Reyes Isabel Rojas Viada Paul Schilke Naparat Suttidate Ana María Venegas Visiting Scientists Alumni Alexander Prishchepov Alexia Sabor Alexandra D Syphard Anna Estes Adrian Lesak Avi Bar Massada Camilo Alcántara Chadwick Rittenhouse Charlotte Gonzalez Abraham Chunguang He David La Puma Elzbieta Laszczak

    Original URL path: http://silvis.forest.wisc.edu/publications/Remote-sensing-vegetation-3-D-structure-biodiversity-and-habitat-Review-and (2015-03-07)
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  • Bird diversity: a predictable function of satellite-derived estimates of seasonal variation in canopy light absorbance across the United States. | SILVIS Lab
    We describe and apply a dynamic habitat index DHI which incorporates three components based on monthly measures of canopy light absorbance through the year The three components are the annual sum the minimum and the seasonal variation in monthly fPAR acquired at a spatial resolution of 1 km over a 6 year period 2000 05 The capacity of these three DHI components to predict bird species richness across 84 defined ecoregions was assessed using regression models Results Total bird species richness showed the highest correlation with the composite DHI R2 0 88 P 0 001 standard error of estimate SE 8 species followed by canopy nesters R2 0 79 P 0 001 SE 3 species and grassland species R2 0 74 P 0 001 SE 1 species Overall the seasonal variation in fPAR compared with the annual average fPAR and its spatial variation across the landscape were the components that accounted for most R2 0 55 0 88 of the observed variation in bird species richness Main conclusions The strong relationship between the DHI and observed avian biodiversity suggests that seasonal and interannual variation in remotely sensed fPAR can provide an effective tool for predicting patterns of avian species richness at regional and broader scales across the conterminous USA Coops 2009 JBioGeog pdf HOME PEOPLE Faculty Anna M Pidgeon Volker C Radeloff Staff David Helmers Nicholas Keuler Shelley Schmidt Post Docs Research Scientists Teri Allendorf Andrew Allstadt Brooke Bateman Eugenia Bragina Sebastian Martinuzzi Eric Wood Graduate Students Patricia Alexandre James Burnham Sarah Carter Diana Guzmán Colón Jessica Gorzo Chris Hamilton Max Henschell Catalina Munteanu Carlos Ramirez Reyes Isabel Rojas Viada Paul Schilke Naparat Suttidate Ana María Venegas Visiting Scientists Alumni Alexander Prishchepov Alexia Sabor Alexandra D Syphard Anna Estes Adrian Lesak Avi Bar Massada Camilo Alcántara Chadwick Rittenhouse Charlotte Gonzalez

    Original URL path: http://silvis.forest.wisc.edu/publications/Bird-diversity-predictable-function-satellite-derived-estimates-seasonal-variation (2015-03-07)
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  • Demographic trends, the Wildland-Urban Interface, and wildfire management. | SILVIS Lab
    urban interface WUI Although population growth has had an impact on the emergence of the WUI the deconcentration of population and housing amenity driven population growth in select nonmetropolitan counties and interregional population shifts to the West and Southeast have had and will continue to have much greater impacts In the coming decades we can expect the retirement of the baby boom generation to exacerbate these trends Hammer 2009 SocNatRes pdf HOME PEOPLE Faculty Anna M Pidgeon Volker C Radeloff Staff David Helmers Nicholas Keuler Shelley Schmidt Post Docs Research Scientists Teri Allendorf Andrew Allstadt Brooke Bateman Eugenia Bragina Sebastian Martinuzzi Eric Wood Graduate Students Patricia Alexandre James Burnham Sarah Carter Diana Guzmán Colón Jessica Gorzo Chris Hamilton Max Henschell Catalina Munteanu Carlos Ramirez Reyes Isabel Rojas Viada Paul Schilke Naparat Suttidate Ana María Venegas Visiting Scientists Alumni Alexander Prishchepov Alexia Sabor Alexandra D Syphard Anna Estes Adrian Lesak Avi Bar Massada Camilo Alcántara Chadwick Rittenhouse Charlotte Gonzalez Abraham Chunguang He David La Puma Elzbieta Laszczak Emily Duerr Frederic Beaudry Glen Aronson Gregory Gavier Pizarro Jodi S Brandt Katarzyna Ostapowicz Kelly Wendland Marty Pfeiffer Matthias Baumann Maxim Dubinin Oscar Cardenas Patrick Culbert Sarahy Contreras Steve Wangen Thomas Albright Tobias Kuemmerle

    Original URL path: http://silvis.forest.wisc.edu/publications/Demographic-trends-Wildland-Urban-Interface-and-wildfire-management (2015-03-07)
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  • Housing growth, forests, and public lands in Northern Wisconsin from 1940 to 2000 | SILVIS Lab
    estimates with the 1992 1993 National Land Cover Dataset to examine the relationship between rural sprawl and land cover especially forests Between 1940 and 2000 private land with 2 housing units km2 decreased from 47 to 21 of the total landscape Most importantly housing growth was concentrated along the boundaries of public lands In 14 of the 19 counties that we studied housing growth rates within 1 km of a public land boundary exceeded growth rates in the remainder of the county and three of the five counties that did not exhibit this pattern were the ones with the least amount of public land Future growth can be expected in areas with abundant natural amenities highlighting the critical need for additional research and effective natural resource management and regional planning to address these challenges Hammer etal JEM 2010 pdf HOME PEOPLE Faculty Anna M Pidgeon Volker C Radeloff Staff David Helmers Nicholas Keuler Shelley Schmidt Post Docs Research Scientists Teri Allendorf Andrew Allstadt Brooke Bateman Eugenia Bragina Sebastian Martinuzzi Eric Wood Graduate Students Patricia Alexandre James Burnham Sarah Carter Diana Guzmán Colón Jessica Gorzo Chris Hamilton Max Henschell Catalina Munteanu Carlos Ramirez Reyes Isabel Rojas Viada Paul Schilke Naparat Suttidate

    Original URL path: http://silvis.forest.wisc.edu/publications/Housing-growth-forests-and-public-lands-Northern-Wisconsin-1940-2000 (2015-03-07)
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  • Land cover mapping of large areas using support vector machines for a chain classification of neighboring Landsat satellite images. | SILVIS Lab
    overlapping areas of neighboring scenes The basic idea was to classify one Landsat scene first where good ground truth data is available and then to classify the neighboring Landsat scene using the land cover classification of the first scene in the overlap area as training data We tested chain classification for a forest non forest classification in the Carpathian Mountains on one horizontal chain of six Landsat scenes and two vertical chains of two Landsat scenes each We collected extensive training data from Quickbird imagery for classifying radiometrically uncorrected data with Support Vector Machines SVMs The SVMs classified 8 scenes with overall accuracies between 92 1 and 98 9 average of 96 3 Accuracy loss when automatically classifying neighboring scenes with chain classification was 1 9 on average Even a chain of six images resulted only in an accuracy loss of 5 1 for the last image compared to a reference classification from independent training data for the last image Chain classification thus performed well but we note that chain classification can only be applied when land cover classes are well represented in the overlap area of neighboring Landsat scenes As long as this constraint is met though chain classification is a powerful approach for large area land cover classifications especially in areas of varying training data availability Knorn 2009 RSE pdf HOME PEOPLE Faculty Anna M Pidgeon Volker C Radeloff Staff David Helmers Nicholas Keuler Shelley Schmidt Post Docs Research Scientists Teri Allendorf Andrew Allstadt Brooke Bateman Eugenia Bragina Sebastian Martinuzzi Eric Wood Graduate Students Patricia Alexandre James Burnham Sarah Carter Diana Guzmán Colón Jessica Gorzo Chris Hamilton Max Henschell Catalina Munteanu Carlos Ramirez Reyes Isabel Rojas Viada Paul Schilke Naparat Suttidate Ana María Venegas Visiting Scientists Alumni Alexander Prishchepov Alexia Sabor Alexandra D Syphard Anna Estes Adrian Lesak

    Original URL path: http://silvis.forest.wisc.edu/publications/Land-cover-mapping-large-areas-using-support-vector-machines-chain-classification (2015-03-07)
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