Forests of the Tanana Valley State Forest and Tetlin National Wildlife Refuge, Alaska: results of the 2014 pilot inventory

Pattison, Robert R.; Andersen, Hans‐Erik; Gray, Andrew N.; Schulz, Bethany K.; Smith, Robert J.; Jovan, Sarah

doi:10.2737/pnw-gtr-967

Cited by 11 publications

(8 citation statements)

References 69 publications

(104 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Tetlin NWR is currently dominated by forests (73%) that are predominately composed of black spruce stands (69% of forest). White spruce stands (10%) occur on better-drained south and west facing hills and along the margins of waterbodies where underlying permafrost is limited [62]. These spruce-dominated forests could be maintained, especially in cool, moist, or higher elevation locations [63].…”

Section: Spruce-dominated Boreal Forest Trajectoriesmentioning

confidence: 99%

See 1 more Smart Citation

A Multi-Scale Blueprint for Building the Decision Context to Implement Climate Change Adaptation on National Wildlife Refuges in the United States

Magness

Wagener

Yurcich

et al. 2022

Earth

View full text Add to dashboard Cite

Climate change and ecological transformation are causing natural resource management to be applied to nonstationary systems. Managers can respond to dynamic ecosystems by resisting, accepting, or directing ecological change. Management response is constrained by a decision context, defined as an interconnected social system of values, rules, and knowledge that affects how problems can be addressed. We provide a multi-scale blueprint for creating a decision context that increases capacity for implementing climate adaptation, including novel approaches in the National Wildlife Refuge System, a continental conservation network administered by the U.S. Fish and Wildlife Service. We use the Tetlin National Wildlife Refuge in Alaska as case study to illustrate blueprint concepts and to provide “proof-of-concept” for application. The blueprint builds on ideas and practices from scenario planning, adaptive management, and adaptive pathway planning, which are approaches that promote action in the face of uncertainty. Management considerations focus on stewarding biodiversity in a changing climate by addressing what futures are possible, what interventions can be used to shape future conditions, and how to coordinate a regional conservation strategy. The blueprint focus on decision context promotes a longer-term social process of engagement that is complementary to, but larger than, any one decision process.

show abstract

Section: Spruce-dominated Boreal Forest Trajectoriesmentioning

confidence: 99%

“…Alaska birch (Betula neoalaskana) stands currently occupy 20% of the Tetlin NWR and quaking aspen (Populus tremuloides) and balsam poplar (Populus balsamifera) trees are present in the landscape [62]. Black spruce forests, currently occupying 69% of the refuge, can shift to deciduous after a high severity fire.…”

Section: Deciduous Dominated Forest Trajectoriesmentioning

confidence: 99%

A Multi-Scale Blueprint for Building the Decision Context to Implement Climate Change Adaptation on National Wildlife Refuges in the United States

Magness

Wagener

Yurcich

et al. 2022

Earth

View full text Add to dashboard Cite

show abstract

“…Nevertheless, in 2014, Congress formally recognized the value of ecosystem services provided by the region and issued guidance and funding for the USDA Forest Service Pacific Northwest Research Station to begin a systematic inventory in interior Alaska. The interior Alaska FIA project began that same year as a pilot study that established 99 plots throughout the Tanana Valley State Forest and Tetlin National Wildlife Refuge (Pattison et al 2018), with the dual goals of assessing the feasibility of field protocols and providing proof of concept that an accurate inventory could be executed in a logistically challenging region (see "Successful Interagency Partnerships in Interior Alaska" on page 10).…”

Section: Forest Inventory and Analysis In Interior Alaskamentioning

confidence: 99%

Forest resources of the Tanana unit, Alaska: 2018

Legner,

Winton,

Dubois

et al. 2022

View full text Add to dashboard Cite

In accordance with Federal civil rights law and U.S. Department of Agriculture (USDA) civil rights regulations and policies, the USDA, its Agencies, offices, and employees, and institutions participating in or administering USDA programs are prohibited from discriminating based on race, color, national origin, religion, sex, gender identity (including gender expression), sexual orientation, disability, age, marital status, family/parental status, income derived from a public assistance program, political beliefs, or reprisal or retaliation for prior civil rights activity, in any program or activity conducted or funded by USDA (not all bases apply to all programs). Remedies and complaint filing deadlines vary by program or incident.Persons with disabilities who require alternative means of communication for program information (e.g., Braille, large print, audiotape, American Sign Language, etc.) should contact the responsible Agency or USDA's TARGET Center at (202) 720-2600 (voice and TTY) or contact USDA through the Federal Relay Service at (800) 877-8339. Additionally, program information may be made available in languages other than English.To file a program discrimination complaint, complete the USDA Program Discrimination Complaint Form, AD-3027, found online at https://www.usda.gov/oascr/complaint-resolution and at any USDA office or write a letter addressed to USDA and provide in the letter all of the information requested in the form. To request a copy of the complaint form, call (866) 632-9992.

show abstract

“…Parameter ν k is carbon variance for pool k, where k = t, w, and s for tree carbon, down woody material carbon, and soil carbon variances, respectively; ρ k is the lidar correlation coefficient for pool k, where k = t, w, and s for tree carbon, DWM carbon, and soil carbon correlations; and Z is the maximum number of lidar plots that can fit into the 13.7 million hectare area (assumed to be one per ha). We calculated the carbon variances and lidar correlations based on a preliminary analysis of tree carbon, down woody material carbon, and soil carbon using a pilot field and lidar dataset in the Tanana valley of interior Alaska [16]. Our estimates for tree carbon, down woody material carbon, and soil carbon variances were 845.8, 32.4, and 2575.6 Mg/ha, respectively.…”

Section: Values Of Parameters and Constantsmentioning

confidence: 99%

Optimal Survey Design for Forest Carbon Monitoring in Remote Regions Using Multi-Objective Mathematical Programming

Tóth

Oken²,

Stawitz³

et al. 2022

Forests

Self Cite

View full text Add to dashboard Cite

Cost-effective monitoring of forest carbon resources is critical to the development of national policies and enforcement of international agreements aimed at reducing carbon emissions and mitigating the impacts of climate change. While carbon monitoring systems are often based on national forest inventories (NFI) utilizing a large sample of field plots, in remote regions the lack of transportation infrastructure often requires heavier reliance on remote sensing technologies, such as airborne lidar. The challenge motivating our research is that the efficacy of estimating carbon with lidar varies across the various carbon pools within forest ecosystems. Lidar measurements are typically highly correlated with aboveground tree carbon but are less strongly correlated with other carbon pools, such as down woody materials (DWM) and soil. Field measurements are essential to both (1) estimate soil and DWM carbon directly and (2) develop regression models to estimate tree carbon indirectly using lidar. With limited budgets and time, however, decision makers must find an optimal way to combine field measurements with lidar to minimize standard errors in carbon estimates for the various pools. We introduce a multi-objective binary programming formulation that quantifies the tradeoffs behind the competing objectives of minimizing standard errors for tree carbon, DWM carbon, and soil carbon. Using NFI and airborne lidar data from a remote boreal forest region of interior Alaska, we demonstrate the operational feasibility of the method and suggest that it is generalizable to other carbon sampling projects because of its generic mathematical structure.

show abstract

Forests of the Tanana Valley State Forest and Tetlin National Wildlife Refuge, Alaska: results of the 2014 pilot inventory

Cited by 11 publications

References 69 publications

A Multi-Scale Blueprint for Building the Decision Context to Implement Climate Change Adaptation on National Wildlife Refuges in the United States

A Multi-Scale Blueprint for Building the Decision Context to Implement Climate Change Adaptation on National Wildlife Refuges in the United States

Forest resources of the Tanana unit, Alaska: 2018

Optimal Survey Design for Forest Carbon Monitoring in Remote Regions Using Multi-Objective Mathematical Programming

Contact Info

Product

Resources

About