White Pine in the Northern Forests: An Ecological and Management History of White Pine on the Bad River Reservation of Wisconsin

Steen-Adams, Michelle M.; Langston, Nancy; Mladenoff, David J.

doi:10.1093/envhis/12.3.614

Cited by 17 publications

(22 citation statements)

References 18 publications

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“…Catastrophic slash fires (1890-1893 and 1908-1910) damaged the soil substrate, compounding the harvest legacy effect (Godfrey 1996, BRNRD 2001. The interaction of reduced seed sources, poor soil conditions, and altered disturbance regime continued to inhibit pine reforestation decades later (Steen-Adams et al 2007). …”

Section: Resultsmentioning

confidence: 99%

“…Policies to retain seed trees (1900)(1901)(1902)(1903)(1904)(1905)(1906)(1907)(1908)(1909), the persistence of refugia pines located on sites inaccessible to harvest, and the program to control the white pine blister rust pathogen (Cronotarium ribocola) combined to present a window of opportunity for restoration ( Fig. 5B; Steen-Adams et al 2007). …”

Section: Resultsmentioning

confidence: 99%

“…First, land fragmentation diminished the cost-effectiveness of the white pine blister rust control program. Forest parcel fragmentation, combined with decreasing labor resources and funding (curtailment of Indian Emergency Conservation Work Program), eventually shut down systematic pathogen control (Steen-Adams et al 2007). In response, foresters shifted from a program that included some (albeit limited) white pine management to one that focused nearly exclusively on even-aged management (aspenpaper birch landscape proportions of 92.5% in 1930 and 72.6% in 1950), to the exclusion of white pine (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Land ownership composition of the Bad River Indian Reservation, Wisconsin, at three times : 1917, 1958, 1986. practice, the application at Bad River did not fit culturally (Godfrey 1996, BRNRD 2001, Doolittle 2001. Clearcuts essentially eliminated reforestation of the historic conifer component (e.g., white pine), a forest type of much greater cultural value to the tribe (BRNRD 2001, Steen-Adams et al 2007). …”

Section: Modernization (1930-1950)mentioning

confidence: 99%

“…We build on our environmental history study of a multipleownership, transitional forest landscape in the northern Great Lakes region (Steen-Adams et al 2007, 2011 to examine how historical contingency conditions CHANS feedbacks. Past research has documented the landscape history of sites historically dominated by eastern white pine (Pinus strobus).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Historical framework to explain long-term coupled human and natural system feedbacks: application to a multiple-ownership forest landscape in the northern Great Lakes region, USA

Steen-Adams¹,

Langston²,

Adams³

et al. 2015

E&S

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Modernization (1930-1950)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Historical framework to explain long-term coupled human and natural system feedbacks: application to a multiple-ownership forest landscape in the northern Great Lakes region, USA

Steen-Adams¹,

Langston²,

Adams³

et al. 2015

E&S

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Spatial multinomial regression models for nominal categorical data: a study of land cover in Northern Wisconsin, USA

et al. 2013

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We develop statistical tools for regression analysis of nominal categorical data on a spatial lattice that are becoming increasingly abundant because of the advances of geographic information systems in environmental science. In a generalized linear mixed model framework, we model the response variable by a multinomial distribution. There are two additive components in the linear predictor: a linear regression on covariates and a spatial random effect such that the spatial dependence in the random effect is induced by a multivariate conditional autoregressive model. Bayesian hierarchical modeling is used for statistical inference, and Markov chain Monte Carlo algorithms are devised to obtain posterior samples. The methodology is applied to analyze a northern Wisconsin land cover data set in a study that assesses the relationship between forest landscape structure and past social conditions, expanding the analytical tools available in landscape ecology and environmental history.

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Composite likelihood estimation for models of spatial ordinal data and spatial proportional data with zero/one values

et al. 2014

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In this paper, we consider a spatial ordered probit model for analyzing spatial ordinal data with two or more ordered categories and, further, a spatial Tobit model for spatial proportional data with zero/one values. We develop a composite likelihood approach for parameter estimation and inference, which aims to balance statistical efficiency and computational efficiency for large datasets. The parameter estimates are obtained by maximizing a composite likelihood function via a quasi‐Newton algorithm. The asymptotic properties of the maximum composite likelihood estimates are established under suitable regularity conditions. An estimate of the inverse of the Godambe information matrix is used for computing the standard errors, and the computation is further expedited by parallel computing. A simulation study is conducted to evaluate the performance of the proposed methods, followed by a real ecological data example. The connections between the spatial ordered probit model and the spatial Tobit model are explored using both simulated and real data. Copyright © 2014 John Wiley & Sons, Ltd.

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White Pine in the Northern Forests: An Ecological and Management History of White Pine on the Bad River Reservation of Wisconsin

Cited by 17 publications

References 18 publications

Historical framework to explain long-term coupled human and natural system feedbacks: application to a multiple-ownership forest landscape in the northern Great Lakes region, USA

Historical framework to explain long-term coupled human and natural system feedbacks: application to a multiple-ownership forest landscape in the northern Great Lakes region, USA

Spatial multinomial regression models for nominal categorical data: a study of land cover in Northern Wisconsin, USA

Composite likelihood estimation for models of spatial ordinal data and spatial proportional data with zero/one values

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