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USGS2016

Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland

Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depend on forest type.

Alaska↗

USGS2014

Thresholds for protecting Pacific Northwest ecosystems from atmospheric deposition of nitrogen: state of knowledge report

The National Park Service and U.S. Forest Service manage areas in the states of Idaho, Oregon, and Washington – collectively referred to in this report as the Pacific Northwest - that contain significant natural resources and provide many recreational opportunities. The agencies are mandated to protect the air quality and air pollution-sensitive resources on these federal lands. Human activity has greatly increased the amount of nitrogen emitted to the atmosphere, resulting in elevated amounts of nitrogen being deposited in park and forest ecosystems. There is limited information in the Pacific Northwest about the levels of nitrogen that negatively affect natural systems, i.e., the critical loads. The National Park Service and U.S. Forest Service, with scientific input from the U.S. Geological Survey, have developed an approach for accumulating additional nitrogen critical loads information in the Pacific Northwest and using the data in planning and regulatory arenas. As a first step in that process, this report summarizes the current state of knowledge about nitrogen deposition, effects, and critical loads in the region. It also describes ongoing research efforts and identifies and prioritizes additional data needs.

Idaho;Oregon;Washington↗

USGS2008

Uncertainty and sensitivity issues in process-based models of carbon and nitrogen cycles in terrestrial ecosystems

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for northern forest ecosystems. These models are widely used to evaluate the long-term decisions in forest management dealing with effects like particulate pollution, productivity and climate change. Regarding climate change, one of the key questions that have sensitive political implications is whether northern forests will sequester atmospheric C or not. Whilst many process-based models have been tested for accuracy by evaluating or validating against observed data, few have dealt with the complexity of the incorporated procedures to estimate uncertainties associated with model predictions or the sensitivity of these predictions to input factors in a systematic, inter-model comparison fashion. In general, models differ in their underlying attempts to match natural complexities with assumed or imposed model structure and process formulations to estimate model parameters, to gather data and to address issues on scope, scale and natural variations. Uncertainties may originate from model structure, estimation of model parameters, data input, representation of natural variation and scaling exercises. Model structure relates to the mathematical representation of the processes modelled and the type of state variables that a model contains. The modelling of partitioning among above- and below-ground C and N pools and the interdependence among these pools remain a major source of uncertainty in model structure and error propagation. For example, most soil C models use at least three state variables to represent the different types of soil organic matter (SOM). This approach results in creating three artificial SOM pools, assuming that each one contains C compounds with the same turnover rate. In reality, SOM consists of many different types of C compounds with widely different turnover rates. Uncertainty in data and parameter estimates are closely linked. Data uncertainties are associated with high variations in estimating forest biomass, productivity and soil organic matter and their estimates may be incomplete for model initialisation, calibration, validation and sensitivity analysis of generalised predictor models. The scale at which a model is being used also affects the level of uncertainty, as the errors in the prediction of the C and N dynamics differ from site to landscape levels and across climatic regions. If the spatial or temporal scale of a model application is changed, additional uncertainty arises from neglecting natural variability in system variables in time and space. Uncertainty issues are also intimately related to model validation and sensitivity analysis. The estimation of uncertainties is needed to inform decision processes in order to detect the possible corridor of development. Uncertainty in this context is an essential measure of quality for stakeholder and decision makers.

Book chapter↗

USGS2018

Thinning, tree-growth, and resistance to multi-year drought in a mixed-conifer forest of northern California

Drought is an important stressor in forest ecosystems that can influence tree vigor and survival. In the U.S., forest managers use two primary management techniques to promote resistance and resilience to drought: prescribed fire and mechanical thinning. Generally applied to reduce fuels and fire hazard, treatments may also reduce competition for resources that may improve tree-growth and reduce mortality during drought. A recent severe and prolonged drought in California provided a natural experiment to investigate tree-growth responses to fuel treatments and climatic stress. We assessed tree-growth from 299 ponderosa pine ( Pinus ponderosa ) and Douglas-fir ( Pseudotsuga menziesii ) in treated and untreated stands during severe drought from 2012 to 2015 in the mixed-conifer forests of Whiskeytown National Recreation Area (WNRA) in northern California. The treatment implemented at WNRA removed 34% of live basal area through mechanical thinning with a subsequent pile burning of residual fuels. Tree-growth was positively associated with crown ratio and negatively associated with competition and a 1-year lag of climate water deficit, an index of drought. Douglas-fir generally had higher annual growth than ponderosa pine, although factors affecting growth were the same for both species. Drought resistance, expressed as the ratio between mean growth during drought and mean growth pre-drought, was higher in treated stands compared to untreated stands during both years of severe drought (2014 and 2015) for ponderosa pine but only one year (2014) for Douglas-fir. Thinning improved drought resistance, but tree size, competition and species influenced this response. On-going thinning treatments focused on fuels and fire hazard reduction are likely to be effective at promoting growth and greater drought resistance in dry mixed-conifer forests. Given the likelihood of future droughts, land managers may choose to implement similar treatments to reduce potential impacts.

Forest Ecology and Management↗

USGS2022

Landscape-scale forest restoration decreases vulnerability to drought mortality under climate change in southwest USA ponderosa forest

Drought-induced tree mortality is predicted to increase in dry forests across the western USA as future projections show hotter, drier climates potentially resulting in large-scale tree die-offs, changes in species composition, and loss of forest ecosystem services, including carbon storage. While some studies have found that forest stands with greater basal areas (BA) have higher drought mortality, many have not evaluated the extent to which forest structure, either overly dense forests due to fire suppression or forests restored to lower densities, interacts with drought mortality. The southwestern USA is particularly susceptible to tree mortality due to the predicted increases in temperature, drier soils, and forests with high density. Our objective was to evaluate how ponderosa pine mortality is expected to be influenced by the Four Forests Restoration Initiative, a large-scale forest restoration effort ongoing in northern Arizona, USA, that will reduce stand BA by approximately 40%. Specifically, we modeled drought mortality in three time periods, one contemporary (1970-2010), and two future (2020-2059 and 2060-2099) under three restoration scenarios: no thinning, 4FRI thinning, and a BA reduction beyond the 4FRI plan (4FRI-intensive). We estimated mortality using 11 climate models under two emissions scenarios. Without thinning, our model predicted that by mid-century (2020-2059), changes in climate could increase annual ponderosa pine mortality rates by 45-57% over contemporary rates. However, with thinning, mid-century mortality was predicted to remain near or below contemporary rates and these rates are 31-35% (4FRI) and 46-51% (4FRI-intensive) less than the mid-century scenarios without thinning. Our study shows that while climate change is likely to increase tree mortality rates, large-scale forest restoration projects, such as 4FRI, have the potential to ameliorate the effects of climate change and keep mortality rates near contemporary levels for decades.

Arizona↗

USGS2010

Shifting microbial community structure across a marine terrace grassland chronosequence, Santa Cruz, California

Changes in the biomass and structure of soil microbial communities have the potential to impact ecosystems via interactions with plants and weathering minerals. Previous studies of forested long-term (1000s – 100,000s of years) chronosequences suggest that surface microbial communities change with soil age. However, significant gaps remain in our understanding of long-term soil microbial community dynamics, especially for non-forested ecosystems and in subsurface soil horizons. We investigated soil chemistry, aboveground plant productivity, and soil microbial communities across a grassland chronosequence (65,000–226,000 yrs old) located near Santa Cruz, CA. Aboveground net primary productivity (ANPP) initially increased to a maximum and then decreased for the older soils. We used polar lipid fatty acids (PLFA) to investigate microbial communities including both surface (<0.1 m) and subsurface (≥0.2 m) soil horizons. PLFAs characteristic of Gram-positive bacteria and actinobacteria increased as a fraction of the microbial community with depth while the fungal fraction decreased relative to the surface. Differences among microbial communities from each chronosequence soil were found primarily in the subsurface where older subsurface soils had smaller microbial community biomass, a higher proportion of fungi, and a different community structure than the younger subsurface soil. Subsurface microbial community shifts in biomass and community structure correlated with, and were likely driven by, decreasing soil P availability and Ca concentrations, respectively. Trends in soil chemistry as a function of soil age led to the separation of the biological (≤1 m depth) and geochemical (>1 m) cycles in the old, slowly eroding landscape we investigated, indicating that this separation, commonly observed in tropical and subtropical ecosystems, can also occur in temperate climates. This study is the first to investigate subsurface microbial communities in a long-term chronosequence. Our results highlight connections between soil chemistry and both the aboveground and belowground parts of an ecosystem.

California↗

USGS2009

Indicators of biodiversity and ecosystem services: A synthesis across ecosystems and spatial scales

According to the Millennium Ecosystem Assessment, common indicators are needed to monitor the loss of biodiversity and the implications for the sustainable provision of ecosystem services. However, a variety of indicators are already being used resulting in many, mostly incompatible, monitoring systems. In order to synthesise the different indicator approaches and to detect gaps in the development of common indicator systems, we examined 531 indicators that have been reported in 617 peer-reviewed journal articles between 1997 and 2007. Special emphasis was placed on comparing indicators of biodiversity and ecosystem services across ecosystems (forests, grass- and shrublands, wetlands, rivers, lakes, soils and agro-ecosystems) and spatial scales (from patch to global scale). The application of biological indicators was found most often focused on regional and finer spatial scales with few indicators applied across ecosystem types. Abiotic indicators, such as physico-chemical parameters and measures of area and fragmentation, are most frequently used at broader (regional to continental) scales. Despite its multiple dimensions, biodiversity is usually equated with species richness only. The functional, structural and genetic components of biodiversity are poorly addressed despite their potential value across habitats and scales. Ecosystem service indicators are mostly used to estimate regulating and supporting services but generally differ between ecosystem types as they reflect ecosystem-specific services. Despite great effort to develop indicator systems over the past decade, there is still a considerable gap in the widespread use of indicators for many of the multiple components of biodiversity and ecosystem services, and a need to develop common monitoring schemes within and across habitats. Filling these gaps is a prerequisite for linking biodiversity dynamics with ecosystem service delivery and to achieving the goals of global and sub-global initiatives to halt the loss of biodiversity. ?? 2009 Oikos.

Oikos↗

USGS2013

Management, morphological, and environmental factors influencing Douglas-fir bark furrows in the Oregon Coast Range

Many land managers in the Pacific Northwest have the goal of increasing late-successional forest structures. Despite the documented importance of Douglas-fir tree bark structure in forested ecosystems, little is known about factors influencing bark development and how foresters can manage development. This study investigated the relative importance of tree size, growth, environmental factors, and thinning on Douglas-fir bark furrow characteristics in the Oregon Coast Range. Bark furrow depth, area, and bark roughness were measured for Douglas-fir trees in young heavily thinned and unthinned sites and compared to older reference sites. We tested models for relationships between bark furrow response and thinning, tree diameter, diameter growth, and environmental factors. Separately, we compared bark responses measured on trees used by bark-foraging birds with trees with no observed usage. Tree diameter and diameter growth were the most important variables in predicting bark characteristics in young trees. Measured environmental variables were not strongly related to bark characteristics. Bark furrow characteristics in old trees were influenced by tree diameter and surrounding tree densities. Young trees used by bark foragers did not have different bark characteristics than unused trees. Efforts to enhance Douglas-fir bark characteristics should emphasize retention of larger diameter trees' growth enhancement.

Oregon↗

USGS2021

Drought stress and hurricane defoliation influence mountain clouds and moisture recycling in a tropical forest

Mountain ranges generate clouds, precipitation, and perennial streamflow for water supplies, but the role of forest cover in mountain hydrometeorology and cloud formation is not well understood. In the Luquillo Experimental Forest of Puerto Rico, mountains are immersed in clouds nightly, providing a steady precipitation source to support the tropical forest ecosystems and human uses. A severe drought in 2015 and the removal of forest canopy (defoliation) by Hurricane Maria in 2017 created natural experiments to examine interactions between the living forest and hydroclimatic processes. These unprecedented land-based observations over 4.5 y revealed that the orographic cloud system was highly responsive to local land-surface moisture and energy balances moderated by the forest. Cloud layer thickness and immersion frequency on the mountain slope correlated with antecedent rainfall, linking recycled terrestrial moisture to the formation of mountain clouds; and cloud-base altitude rose during drought stress and posthurricane defoliation. Changes in diurnal cycles of temperature and vapor-pressure deficit and an increase in sensible versus latent heat flux quantified local meteorological response to forest disturbances. Temperature and water vapor anomalies along the mountain slope persisted for at least 12 mo posthurricane, showing that understory recovery did not replace intact forest canopy function. In many similar settings around the world, prolonged drought, increasing temperatures, and deforestation could affect orographic cloud precipitation and the humans and ecosystems that depend on it.

Puerto Rico↗

USGS2010

A model‐data intercomparison of CO2 exchange across North America: Results from the North American Carbon Program site synthesis

Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO 2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO 2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models' ability to simulate the seasonal cycle of CO 2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.

Journal of Geophysical Research: Biogeosciences↗

USGS2025

Satellite-based evidence of recent decline in global forest recovery rate from tree mortality events

Climate-driven forest mortality events have been extensively observed in recent decades, prompting the question of how quickly these affected forests can recover their functionality following such events. Here we assessed forest recovery in vegetation greenness (normalized difference vegetation index) and canopy water content (normalized difference infrared index) for 1,699 well-documented forest mortality events across 1,600 sites worldwide. By analysing 158,427 Landsat surface reflectance images sampled from these sites, we provided a global assessment on the time required for impacted forests to return to their pre-mortality state (recovery time). Our findings reveal a consistent decline in global forest recovery rate over the past decades indicated by both greenness and canopy water content. This decline is particularly noticeable since the 1990s. Further analysis on underlying mechanisms suggests that this reduction in global forest recovery rates is primarily associated with rising temperatures and increased water scarcity, while the escalation in the severity of forest mortality contributes only partially to this reduction. Moreover, our global-scale analysis reveals that the recovery of forest canopy water content lags significantly behind that of vegetation greenness, implying that vegetation indices based solely on greenness can overestimate post-mortality recovery rates globally. Our findings underscore the increasing vulnerability of forest ecosystems to future warming and water insufficiency, accentuating the need to prioritize forest conservation and restoration as an integral component of efforts to mitigate climate change impacts.

Nature Plants↗

USGS2011

Estimating riparian understory vegetation cover with beta regression and copula models

Understory vegetation communities are critical components of forest ecosystems. As a result, the importance of modeling understory vegetation characteristics in forested landscapes has become more apparent. Abundance measures such as shrub cover are bounded between 0 and 1, exhibit heteroscedastic error variance, and are often subject to spatial dependence. These distributional features tend to be ignored when shrub cover data are analyzed. The beta distribution has been used successfully to describe the frequency distribution of vegetation cover. Beta regression models ignoring spatial dependence (BR) and accounting for spatial dependence (BRdep) were used to estimate percent shrub cover as a function of topographic conditions and overstory vegetation structure in riparian zones in western Oregon. The BR models showed poor explanatory power (pseudo-R 2 ≤ 0.34) but outperformed ordinary least-squares (OLS) and generalized least-squares (GLS) regression models with logit-transformed response in terms of mean square prediction error and absolute bias. We introduce a copula (COP) model that is based on the beta distribution and accounts for spatial dependence. A simulation study was designed to illustrate the effects of incorrectly assuming normality, equal variance, and spatial independence. It showed that BR, BRdep, and COP models provide unbiased parameter estimates, whereas OLS and GLS models result in slightly biased estimates for two of the three parameters. On the basis of the simulation study, 93–97% of the GLS, BRdep, and COP confidence intervals covered the true parameters, whereas OLS and BR only resulted in 84–88% coverage, which demonstrated the superiority of GLS, BRdep, and COP over OLS and BR models in providing standard errors for the parameter estimates in the presence of spatial dependence.

Forest Science↗

USGS2003

Isotopic composition of carbon dioxide from a boreal forest fire: Inferring carbon loss from measurements and modeling

Fire is an important pathway for carbon (C) loss from boreal forest ecosystems and has a strong effect on ecosystem C balance. Fires can range widely in severity, defined as the amount of vegetation and forest floor consumed by fire, depending on local fuel and climatic conditions. Here we explore a novel method for estimating fire severity and loss of C from fire using the atmosphere to integrate ecosystem heterogeneity at the watershed scale. We measured the δ 13 C and Δ 14 C isotopic values of CO 2 emitted from an experimental forest fire at the Caribou-Poker Creek Research Watershed (CPCRW), near Fairbanks, Alaska. We used inverse modeling combined with dual isotope measurements of C contained in aboveground black spruce biomass and soil organic horizons to estimate the amount of C released by this fire. The experimental burn was a medium to severe intensity fire that released, on average, about 2.5 kg Cm −2 , more than half of the C contained in vegetation and soil organic horizon pools. For vegetation, the model predicted that approximately 70–75% of pools such as needles, fine branches, and bark were consumed by fire, whereas only 20–30% of pools such as coarse branches and cones were consumed. The fire was predicted to have almost completely consumed surface soil organic horizons and burned about half of the deepest humic horizon. The ability to estimate the amount of biomass combusted and C emission from fires at the watershed scale provides an extensive approach that can complement more limited intensive ground-based measurements.

Alaska↗

USGS2017

Rapid colonization of a Hawaiian restoration forest by a diverse avian community

Deforestation of tropical forests has led to widespread loss and extirpation of forest bird species around the world, including the Hawaiian Islands which have experienced a dramatic loss of forests over the last 200–800 years. Given the important role birds play in forest ecosystem functions via seed dispersal and pollination, a bird community's response to forest restoration is an important measure of the success of such conservation actions. We evaluated the bird response to reforestation at an important bird sanctuary, Hakalau Forest National Wildlife Refuge, Hawai′i Island, using 26 years of bird count data. We show that most species from within the diverse avian community increased significantly, but species colonized the restoration forest at different rates. Distance from intact forest and time since restoration were both important predictors of colonization rate, interacting such that for most species it took more time to colonize areas farther from the intact forest. In addition, both forest cover and understory diversity helped to explain bird densities, but the effect varied among species, suggesting that different habitat requirements may help drive variation in colonization rates. This article provides the first detailed evaluation of how a diverse community of birds has responded to one of the largest, ongoing reforestation projects in Hawai′i.

Hawai′i↗

USGS1997

Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within the wet conifer mosaic. Major differences in the 1-km AVHRR and 30-m Landsat TM-derived land cover classes are most likely due to differences in the spatial resolution of the data sets. In general, the 1 km AVHRR land cover classes are vegetation mosaics consisting of mixed combinations of the Landsat classes. Detailed mapping of the global boreal forest with this approach will benefit from algorithms for cloud screening and to atmospherically correct reflectance data for both aerosol and water vapor effects. We believe that this 1 km AVHRR land cover analysis provides new and useful information for regional water, energy, carbon, and trace gases studies in BOREAS, especially given the significant spatial variability in land cover type and associated biophysical land cover parameters (e.g., albedo, leaf area index, FPAR, and surface roughness). Multiresolution land cover comparisons (30 m, 1 km, and 100 km grid cells) also illustrated how heterogeneous landscape patterns are represented in land cover maps with differing spatial scales and provided insights on the requirements and challenges for parameterizing landscape heterogeneity as part of land surface process research.

Journal of Geophysical Research D: Atmospheres↗

USGS2013

High-resolution global maps of 21st-century forest cover change

Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil’s well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

Science↗

USGS2016

Soil data for a vegetation gradient located at Bonanza Creek Long Term Ecological Research Site, interior Alaska

Boreal soils play an important role in the global carbon cycle owing to the large amount of carbon stored within this northern region. To understand how carbon and nitrogen storage varied among different ecosystems, a vegetation gradient was established in the Bonanza Creek Long Term Ecological Research (LTER) site, located in interior Alaska. The ecosystems represented are a black spruce ( Picea mariana )–feather moss (for example, Hylocomium sp.) forest ecosystem, a shrub-dominated ecosystem, a tussock-grass-dominated ecosystem, a sedge-dominated ecosystem, and a rich fen ecosystem. Here, we report the physical, chemical, and descriptive properties for the soil cores collected at these sites. These data have been used to calculate carbon and nitrogen accumulation rates on a long-term (decadal and century) basis (Manies and others, in press).

Open-File Report↗

USGS2020

Forest management and bats

Because more than half of the forest land in the United States is privately owned, forest landowners play an important role in the stewardship of our wildlife resources. This publication will introduce you to a group of wildlife that is particularly important to forest ecosystems, but also one of the most misunderstood: bats. We will demonstrate how active forest management can improve forest health and productivity while maintaining and enhancing habitat for these fascinating and beneficial mammals.

Report↗