Diadromous aquatic species that cross a diverse range of habitats (including marine, estuarine, and freshwater) face different effects of climate change in each environment. One such group of species is the anadromous Pacific salmon (Oncorhynchus spp.). Studies of the potential effects of climate change on salmonids have focused on both marine and freshwater environments. Access to a variety of estuarine habitat has been shown to enhance juvenile life-history diversity, thereby contributing to the resilience of many salmonid species. Our study is focused on the effect of sea-level rise on the availability, complexity, and distribution of estuarine, and low-freshwater habitat for Chinook salmon (Oncorhynchus tshawytscha), steelhead (anadromous O. mykiss), and coho salmon (O. kisutch) along the Oregon Coast under future climate change scenarios. Using LiDAR, we modeled the geomorphologies of five Oregon estuaries and estimated a contour associated with the current mean high tide. Contour intervals at 1- and 2-m increments above the current mean high tide were generated, and changes in the estuary morphology were assessed. Because our analysis relied on digital data, we compared three types of digital data in one estuary to assess the utility of different data sets in predicting the changes in estuary shape. For each salmonid species, changes in the amount and complexity of estuarine edge habitats varied by estuary. The simple modeling approach we applied can also be used to identify areas that may be most amenable to pre-emptive restoration actions to mitigate or enhance salmonid habitat under future climatic conditions.
Currently in its third phase, the North American Forest Dynamics (NAFD) project has launched nationwide processing of historic Landsat data to provide a comprehensive annual, wall-to-wall analysis of U.S. disturbance history over the last 30+ years. Because understanding the cause of disturbance is important to quantifying carbon dynamics, work is underway to attribute causal agents to these nationwide change maps. Developing empirical models of the diverse causal agents in this country involves many decisions. Alternative response designs (such as varying size, shape, quantity, and level of detail in training data) are being evaluated in terms of their costs and benefits for national mapping applications. Many classes of predictor variables such as spectral signatures, textural metrics, extant geospatial disturbance libraries, and bioclimatic information, are being tested for their contribution to classification models. Flexible modeling techniques, such as the Random Forests models used here, are powerful predictive tools but must be coupled with simple rule-based models reflecting expert knowledge. And decisions about appropriate modeling subpopulations are being made in light of available training data, diversity of ecological zones, and computational efficiency. We will be synthesizing results from our initial exploratory work as well as from pilot analyses conducted over 10 Landsat TM scenes representing diverse causal agents, forest types, and forest prevalence levels. We also discuss how these causal disturbance models will enable extensive analyses of temporal and spatial patterns in causal agents across the United States.
This synthesis addresses the vulnerability of the North American high-latitude soil organic carbon (SOC) pool to climate change. Disturbances caused by climate warming in arctic, subarctic, and boreal environments can result in significant redistribution of C among major reservoirs with potential global impacts. We divide the current northern high-latitude SOC pools into (1) near-surface soils where SOC is affected by seasonal freeze-thaw processes and changes in moisture status, and (2) deeper permafrost and peatland strata down to several tens of meters depth where SOC is usually not affected by short-term changes. We address key factors (permafrost, vegetation, hydrology, paleoenvironmental history) and processes (C input, storage, decomposition, and output) responsible for the formation of the large high-latitude SOC pool in North America and highlight how climate-related disturbances could alter this pool's character and size. Press disturbances of relatively slow but persistent nature such as top-down thawing of permafrost, and changes in hydrology, microbiological communities, pedological processes, and vegetation types, as well as pulse disturbances of relatively rapid and local nature such as wildfires and thermokarst, could substantially impact SOC stocks. Ongoing climate warming in the North American high-latitude region could result in crossing environmental thresholds, thereby accelerating press disturbances and increasingly triggering pulse disturbances and eventually affecting the C source/sink net character of northern high-latitude soils. Finally, we assess postdisturbance feedbacks, models, and predictions for the northern high-latitude SOC pool, and discuss data and research gaps to be addressed by future research.
The Northwest Forest Plan required the US Forest Service (USFS) to shift its management focus to ecological values rather than the utilitarian ones that had dominated forest policy in the region. This article examines the effects of this shift on the USFS's historic mission to provide recreational access to the region's forests. Focusing on six national forests, it draws on a series of interviews with USFS personnel to answer two questions that explore the persistence of policies across time and the importance of the implementation stage in shaping outcomes. How did the USFS balance a deeply entrenched, institutionalized history of recreational use against new ecological priorities and habitat protection expectations? What were the effects at the local level on recreational use and access in riparian and other ecologically sensitive areas? The findings indicate that despite greater attention to ecological protection, recreation continues to be a priority.
Aquatic ecologists are working to develop theory and techniques for analysis of dynamic stream processes and communities of organisms. Such work is critical for the development of conservation plans that are relevant at the scale of entire ecosystems. The stream network is the foundation upon which stream systems are organized. Natural and human disturbances in streams alter the configuration of stream habitats such as pools, riffles, and glides across seasons, decades, or centuries. Thus, native aquatic species have developed mechanisms for adapting to the dynamic configuration of habitats in stream networks. At different spatial scales, stream network structure informs habitat connectivity for aquatic-obligate species. The movement of aquatic species both upstream and downstream is limited by stream channels and may be modified by the downstream flow of water, nutrients, and physical materials such as wood and substrate. Analysing streams as networks offers a realistic and holistic perspective for assessing movement and distribution by freshwater aquatic species in response to life-history needs and environmental conditions. In this study, network analysis was facilitated by automating, in a Geographic Information System, the calculation of network distances and variables that represent spatial configuration. A comparison between traditional instream habitat variables and network variables for juvenile coho salmon (Oncorhynchus kisutch) in seven sub-basins of Oregon's mid-coast over a 5-year period revealed that network variables perform better at explaining juvenile coho salmon density than in stream habitat variables. Moreover, analysis of network distances among seasonal habitats indicates that juvenile coho salmon density may be higher where the distance between critical seasonal habitats is short. This work furthers aquatic conservation, management, and restoration by including analysis of the proximity and connectivity among aquatic freshwater habitats.
Fire hazard mitigation planning requires an accurate accounting of fuel complexes to predict potential fire behavior and effects of treatment alternatives. In the southeastern United States, rapid vegetation growth coupled with complex land use history and forest management options requires a dynamic approach to fuel characterization. In this study we assessed potential surface fire behavior with the Fuel Characteristic Classification System (FCCS), a tool which uses inventoried fuelbed inputs to predict fire behavior. Using inventory data from 629 plots established in the upper Atlantic Coastal Plain, South Carolina, we constructed FCCS fuelbeds representing median fuel characteristics by major forest type and age class. With a dry fuel moisture scenario and 6.4 km h-1 midflame wind speed, the FCCS predicted moderate to high potential fire hazard for the majority of the fuelbeds under study. To explore fire hazard under potential future fuel conditions, we developed fuelbeds representing the range of quantitative inventory data for fuelbed components that drive surface fire behavior algorithms and adjusted shrub species composition to represent 30% and 60% relative cover of highly flammable shrub species. Results indicate that the primary drivers of surface fire behavior vary by forest type, age and surface fire behavior rating. Litter tends to be a primary or secondary driver in most forest types. In comparison to other surface fire contributors, reducing shrub loading results in reduced flame lengths most consistently across forest types. FCCS fuelbeds and the results from this project can be used for fire hazard mitigation planning throughout the southern Atlantic Coastal Plain where similar forest types occur. The approach of building simulated fuelbeds across the range of available surface fuel data produces sets of incrementally different fuel characteristics that can be applied to any dynamic forest types in which surface fuel conditions change rapidly.
In the southeastern USA, land use history, forest management and natural geomorphic features have created heterogeneous fuel loads. This apparent temporal and spatial variation in fuel loads make it difficult to reliably assess potential fire behavior from remotely sensed canopy variables to determine risk and to prescribe treatments. We examined this variation by exploring the relationships between overstory forest vegetation attributes, recent fire history, and selected surface fuel components across an 80,000 ha contiguous landscape. Measurements of dead and live vegetation components of surface fuels were obtained from 624 permanent plots, or about 1 plot per 100 ha of forest cover. Within forest vegetation groups, we modeled the relationship between individual surface fuel components and overstory stand age, basal area, site quality and recent fire history, then stochastically predicted fuel loads across the landscape using the same linkage variables. The fraction of the plot variation, i.e., R2, explained by predictive models for individual fuel components ranged from 0.05 to 0.66 for dead fuels and 0.03 to 0.97 for live fuels in pine dominated vegetation groups. Stand age and basal area were generally more important than recent fire history for predicting fuel loads. Mapped fuel loads using these regressor variables showed a very heterogeneous landscape even at the scale of a few square kilometers. The mapped patterns corresponded to stand based forest management disturbances that are reflected in age, basal area, and fire history. Recent fire history was significant in explaining variation in litter and duff biomass. Stand basal area was positively and consistently related to dead fuel biomass in most groups and was present in many predictive equations. Patterns in live fuel biomass were related to recent fire history, but the patterns were not consistent among forest vegetation groups. Age and basal area were related to live fuels in a complex manner that is likely confounded with periodic disturbances that disrupt stand dynamics. This study complements earlier hazardous fuels research in the southeastern USA, and indicates that succession, disturbance, site quality and decomposition interact with forest management practices to create variable spatial and temporal conditions. The inclusion of additional land use, disturbance history, and soil-topographic variables coupled to improved sampling methods may increase precision and subsequent fuel mapping.
A century of fire suppression has created heavy fuel loads in many U.S. forests, leading to increasingly intense wildfires. Addressing this problem will require widespread fuels treatments, yet fuels treatment planners do not always have access to the current scientific information that can help guide their planning process. The Fuels Planning: Science Synthesis and Integration project was launched to compile relevant fuels treatment information for managers. Products include syntheses on various topics, a guidebook on silvicultural prescriptions, a set of models and information databases on possible environmental effects of fuels treatments, and a financial analysis tool for estimating costs and revenues of fuels treatments. The Fuels Planning project provides an example of how collaboration between managers and scientists can improve the utility of scientific findings. It is currently forming partnerships with several National Environmental Policy Act (NEPA) interdisciplinary teams who will use these decision support tools in planning fuels reduction projects starting in the summer of 2005.
Big sagebrush (Artemisia tridentata) is one of the most widely distributed and ecologically important shrub species in western North America. This species serves as a critical habitat and food resource for many animals and invertebrates. Habitat loss due to a combination of disturbances followed by establishment of invasive plant species is a serious threat to big sagebrush ecosystem sustainability. Lack of genomic data has limited our understanding of the evolutionary history and ecological adaptation in this species. Here, we report on the sequencing of expressed sequence tags (ESTs) and detection of single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) markers in subspecies of big sagebrush.
Forest-meadow ecotones are prominent and dynamic features of mountain ecosystems. Understanding how vegetation changes are shaped by long-term interactions with trees and are mediated by the physical environment is critical to predicting future trends in biological diversity across these landscapes. We examined 26 yr of vegetation change (1983-2009) across 20 forest-meadow ecotones spanning a range of landforms/hydrologies and elevations (montane and subalpine) in the Three Sisters Biosphere Reserve, Oregon (USA). We quantified changes in tree structure (cover, density, and basal area) and in the abundance and diversity of ground-layer vegetation based on species' habitat associations and growth forms. To explore the contributions of tree structure, landscape context, and initial vegetation to changes in ecotonal communities, we used a combination of NMDS, PCA, and multiple regression. Despite a long history (50-100 yr) of tree invasion, ecotones were still dominated by meadow species in 1983. Ecotones exhibited significant but varying patterns of change over the study period while adjacent forest and meadow habitats remained stable. Despite a significant increase in summer temperature, we found little evidence of a direct influence of climate on ecotonal changes. Declines in total richness, and in the cover and richness of meadow species, were greater where soil moisture was seasonally limiting (montane mesic slopes and subalpine early snowmelt sites). Forest species showed much greater increases in montane than subalpine ecotones; limited colonization of the latter reflects the depauperate nature of subalpine forest understories in this region. Vegetation changes were related to initial tree structure but not to changes in structure over the study period. Past tree invasions, a legacy of both climate variation and disturbance history, continue to exert strong influences on ecotonal ground-layer communities. However, the consequences for local diversity vary across the landscape. Quantifying the nature of this variation through long-term observations is a critical step toward predicting future changes in the biological diversity of these and other mountain ecosystems.