A new approach to evaluate forest structure restoration needs across Oregon and Washington, USA

Widespread habitat degradation and uncharacteristic fire, insect, and disease outbreaks in forests across the western United States have led to highly publicized calls to increase the pace and scale of forest restoration. Despite these calls, we frequently lack a comprehensive understanding of forest restoration needs. In this study we demonstrate a new approach for evaluating where, how much, and what types of restoration are needed to move present day landscape scale forest structure towards a Natural Range of Variability (NRV) across eastern Washington, eastern Oregon, and southwestern Oregon. Our approach builds on the conceptual framework of the LANDFIRE and Fire Regime Condition Class programs. Washington–Oregon specific datasets are used to assess the need for changes to current forest structure resulting from disturbance and/or succession at watershed and regional scales. Across our analysis region we found that changes in current structure would be needed on an estimated 4.7 million+ ha (40% of all coniferous forests) in order to restore forest structure approximating NRV at the landscape scale. Both the overall level and the type of restoration need varied greatly between forested biophysical settings. Regional restoration needs were dominated by the estimated 3.8+ million ha in need of thinning and/or low severity fire in forests that were historically maintained by frequent low or mixed severity fire (historical Fire Regime Group I and III biophysical settings). However, disturbance alone cannot restore NRV forest structure. We found that time to transition into later development structural classes through successional processes was required on approximately 3.2 million ha (over 25% of all coniferous forests). On an estimated 2.3 million ha we identified that disturbance followed by succession was required to restore NRV forest structure. The results of this study are intended to facilitate the ability of local land managers to incorporate regional scale, multi-ownership context into local forest management and restoration. Meeting the region-wide restoration needs identified in this study will require a substantial increase in the pace and scale of restoration treatments and coordination amongst governments, agencies, and landowners.Keywords: Landfire, Fire Regime Condition Class, Gradient nearest neighbor, Natural range of variation, Ecological restoration, Pacific Northwes

Accounting for Ecosystem Alteration Doubles Estimates of Conservation Risk in the Conterminous United States

Previous national and global conservation assessments have relied on habitat conversion data to quantify conservation risk. However, in addition to habitat conversion to crop production or urban uses, ecosystem alteration (e.g., from logging, conversion to plantations, biological invasion, or fire suppression) is a large source of conservation risk. We add data quantifying ecosystem alteration on unconverted lands to arrive at a more accurate depiction of conservation risk for the conterminous United States. We quantify ecosystem alteration using a recent national assessment based on remote sensing of current vegetation compared with modeled reference natural vegetation conditions. Highly altered (but not converted) ecosystems comprise 23% of the conterminous United States, such that the number of critically endangered ecoregions in the United States is 156% higher than when calculated using habitat conversion data alone. Increased attention to natural resource management will be essential to address widespread ecosystem alteration and reduce conservation risk

A state-and-transition simulation modeling approach for estimating the historical range of variability

Reference ecological conditions offer important context for land managers as they assess the condition of their landscapes and provide benchmarks for desired future conditions. State-and-transition simulation models (STSMs) are commonly used to estimate reference conditions that can be used to evaluate current ecosystem conditions and to guide land management decisions and activities. The LANDFIRE program created more than 1,000 STSMs and used them to assess departure from a mean reference value for ecosystems in the United States. While the mean provides a useful benchmark, land managers and researchers are often interested in the range of variability around the mean. This range, frequently referred to as the historical range of variability (HRV), offers model users improved understanding of ecosystem function, more information with which to evaluate ecosystem change and potentially greater flexibility in management options. We developed a method for using LANDFIRE STSMs to estimate the HRV around the mean reference condition for each model state in ecosystems by varying the fire probabilities. The approach is flexible and can be adapted for use in a variety of ecosystems. HRV analysis can be combined with other information to help guide complex land management decisions

Assessing Ecosystem Condition: Use and Customization of the Vegetation Departure Metric

Assessment of ecosystem change often focuses on the degree of conversion and representation in networks of protected areas. While essential, these factors alone do not provide a holistic index of ecosystem conditions. Metrics that compare the current state of ecosystems to a meaningful reference condition can help identify “hidden” risks, lost functions, and provide conservation and management-relevant insights. Here we review a departure metric that can be used to measure ecosystem conditions and its implementation for all lands in the United States by the LANDFIRE Program. We then use two case studies to demonstrate how manually calculating the departure metric is used to explore under- and over-representation of structural stages. Finally, we document the assumptions, interpretation, and limitations of the departure metric, and discuss its current and possible future applications

Assessing Ecosystem Condition: Use and Customization of the Vegetation Departure Metric

Assessment of ecosystem change often focuses on the degree of conversion and representation in networks of protected areas. While essential, these factors alone do not provide a holistic index of ecosystem conditions. Metrics that compare the current state of ecosystems to a meaningful reference condition can help identify “hidden” risks, lost functions, and provide conservation and management-relevant insights. Here we review a departure metric that can be used to measure ecosystem conditions and its implementation for all lands in the United States by the LANDFIRE Program. We then use two case studies to demonstrate how manually calculating the departure metric is used to explore under- and over-representation of structural stages. Finally, we document the assumptions, interpretation, and limitations of the departure metric, and discuss its current and possible future applications

Identifying opportunity hot spots for reducing the risk of wildfire-caused carbon loss in western US conifer forests

The escalating climate and wildfire crises have generated worldwide interest in using proactive forest management (e.g. forest thinning, prescribed fire, cultural burning) to mitigate the risk of wildfire-caused carbon loss in forests. To estimate the risk of wildfire-caused carbon loss in western United States (US) conifer forests, we used a generalizable framework to evaluate interactions among wildfire hazard and carbon exposure and vulnerability. By evaluating where high social adaptive capacity for proactive forest management overlaps with carbon most vulnerable to wildfire-caused carbon loss, we identified opportunity hot spots for reducing the risk of wildfire-caused carbon loss. We found that relative to their total forest area, California, New Mexico, and Arizona contained the greatest proportion of carbon highly vulnerable to wildfire-caused loss. We also observed widespread opportunities in the western US for using proactive forest management to reduce the risk of wildfire-caused carbon loss, with many areas containing opportunities for simultaneously mitigating the greatest risk from wildfire to carbon and human communities. Finally, we highlighted collaborative and equitable processes that provide pathways to achieving timely climate- and wildfire-mitigation goals at opportunity hot spots

A randomized, double-blind, placebo-controlled trial of antidepressants in Parkinson disease

OBJECTIVE: To evaluate the efficacy and safety of a selective serotonin reuptake inhibitor (SSRI) and a serotonin and norepinephrine reuptake inhibitor (SNRI) in the treatment of depression in Parkinson disease (PD). METHODS: A total of 115 subjects with PD were enrolled at 20 sites. Subjects were randomized to receive an SSRI (paroxetine; n = 42), an SNRI (venlafaxine extended release [XR]; n = 34), or placebo (n = 39). Subjects met DSM-IV criteria for a depressive disorder, or operationally defined subsyndromal depression, and scored >12 on the first 17 items of the Hamilton Rating Scale for Depression (HAM-D). Subjects were followed for 12 weeks (6-week dosage adjustment, 6-week maintenance). Maximum daily dosages were 40 mg for paroxetine and 225 mg for venlafaxine XR. The primary outcome measure was change in the HAM-D score from baseline to week 12. RESULTS: Treatment effects (relative to placebo), expressed as mean 12-week reductions in HAM-D score, were 6.2 points (97.5% confidence interval [CI] 2.2 to 10.3, p = 0.0007) in the paroxetine group and 4.2 points (97.5% CI 0.1 to 8.4, p = 0.02) in the venlafaxine XR group. No treatment effects were seen on motor function. CONCLUSIONS: Both paroxetine and venlafaxine XR significantly improved depression in subjects with PD. Both medications were generally safe and well tolerated and did not worsen motor function. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that paroxetine and venlafaxine XR are effective in treating depression in patients with PD