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Modeling habitat of the desert tortoise (Gopherus agassizii) in the Mojave and parts of the Sonoran Deserts of California, Nevada, Utah, and Arizona

Habitat modeling is an important tool used to simulate the potential distribution of a species for a variety of basic and applied questions. The desert tortoise ( Gopherus agassizii ) is a federally listed threatened species in the Mojave Desert and parts of the Sonoran Desert of California, Nevada, Utah, and Arizona. Land managers in this region require reliable information about the potential distribution of desert tortoise habitat to plan conservation efforts, guide monitoring activities, monitor changes in the amount and quality of habitat available, minimize and mitigate disturbances, and ultimately to assess the status of the tortoise and its habitat toward recovery of the species. By applying information from the literature and our knowledge or assumptions of environmental variables that could potentially explain variability in the quality of desert tortoise habitat, we developed a quantitative habitat model for the desert tortoise using an extensive set of field-collected presence data. Sixteen environmental data layers were converted into a grid covering the study area and merged with the desert tortoise presence data that we gathered for input into the Maxent habitat-modeling algorithm. This model provides output of the statistical probability of habitat potential that can be used to map potential areas of desert tortoise habitat. This type of analysis, while robust in its predictions of habitat, does not account for anthropogenic changes that may have altered habitat with relatively high potential into areas with lower potential.

California, Nevada, Utah, Arizona

Proceedings of the Klamath Basin Science Conference, Medford, Oregon, February 1-5, 2010

This report presents the proceedings of the Klamath Basin Science Conference (February 2010). A primary purpose of the meeting was to inform and update Klamath Basin stakeholders about areas of scientific progress and accomplishment during the last 5 years. Secondary conference objectives focused on the identification of outstanding information needs and science priorities as they relate to whole watershed management, restoration ecology, and possible reintroduction of Pacific salmon associated with the Klamath Basin Restoration Agreement (KBRA). Information presented in plenary, technical, breakout, and poster sessions has been assembled into chapters that reflect the organization, major themes, and content of the conference. Chapter 1 reviews the major environmental issues and resource management and other stakeholder needs of the basin. Importantly, this assessment of information needs included the possibility of large-scale restoration projects in the future and lessons learned from a case study in South Florida. Other chapters (2-6) summarize information about key components of the Klamath Basin, support conceptual modeling of the aquatic ecosystem (Chapter 7), and synthesize our impressions of the most pressing science priorities for management and restoration. A wealth of information was presented at the conference and this has been captured in chapters addressing environmental setting and human development of the basin, hydrology, watershed processes, fishery resources, and potential effects from climate change. The final chapter (8) culminates in a discussion of many specific research priorities that relate to and bookend the broader management needs and restoration goals identified in Chapter 1. In many instances, the conferees emphasized long-term and process-oriented approaches to watershed science in the basin as planning moves forward.

California, Oregon

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

Estuaries and Coasts

Post-wildfire landscape change and erosional processes from repeat terrestrial lidar in a steep headwater catchment, Chiricahua Mountains, Arizona, USA

Flooding and erosion after wildfires present increasing hazard as climate warms, semi-arid lands become drier, population increases, and the urban interface encroaches farther into wildlands. We quantify post-wildfire erosion in a steep, initially unchannelized, 7.5 ha headwater catchment following the 2011 Horseshoe 2 Fire in the Chiricahua Mountains of southeastern Arizona. Using time-lapse cameras, rain gauges, and repeat surveys by terrestrial laser scanner, we quantify the response of a burned landscape to subsequent precipitation events. Repeat surveys provide detailed pre-and post-rainfall measurements of landscape form associated with a range of weather events. The first post-fire precipitation led to sediment delivery equivalent to 0.017 m of erosion from hillslopes and 0.12 m of erosion from colluvial hollows. Volumetrically, 69% of sediment yield was generated from hillslope erosion and 31% was generated from gully channel establishment in colluvial hollows. Processes on hillslopes included erosion by extensive shallow overland flow, formation of rills and gullies, and generation of sediment-laden flows and possibly debris flows. Subsequent smaller rain events caused ongoing hillslope erosion and local deposition and erosion in gullies. Winter freeze-thaw led to soil expansion, likely related to frost-heaving, causing a net centimeter-scale elevation increase across soil-mantled slopes. By characterizing landscape form, the properties of near-surface materials, and measuring both precipitation and landscape change, we can improve our empirical understanding of landscape response to environmental forcing. This detailed approach to studying landscape response to wildfires may be useful in the improvement of predictive models of flood, debris flow and sedimentation hazards used in post-wildfire response assessments and land management, and may help improve process-based models of landscape evolution.

Arizona

Modeling of soil erosion and sediment transport in the East River Basin in southern China

Soil erosion is a major global environmental problem that has caused many issues involving land degradation, sedimentation of waterways, ecological degradation, and nonpoint source pollution. Therefore, it is significant to understand the processes of soil erosion and sediment transport along rivers, and this can help identify the erosion prone areas and find potential measures to alleviate the environmental effects. In this study, we investigated soil erosion and identified the most seriously eroded areas in the East River Basin in southern China using a physically-based model, Soil and Water Assessment Tool (SWAT). We also introduced a classical sediment transport method (Zhang) into SWAT and compared it with the built-in Bagnold method in simulating sediment transport process along the river. The derived spatial soil erosion map and land use based erosion levels can explicitly illustrate the identification and prioritization of the critical soil erosion areas in this basin. Our results also indicate that erosion is quite sensitive to soil properties and slope. Comparison of Bagnold and Zhang methods shows that the latter can give an overall better performance especially in tracking the peak and low sediment concentrations along the river. We also found that the East River is mainly characterized by sediment deposition in most of the segments and at most times of a year. Overall, the results presented in this paper can provide decision support for watershed managers about where the best management practices (conservation measures) can be implemented effectively and at low cost. The methods we used in this study can also be of interest in sediment modeling for other basins worldwide.

Science of the Total Environment

Can we avert an Amazon tipping point? The economic and environmental costs

The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.

Amazon

The Massachusetts Sustainable-Yield Estimator: A decision-support tool to assess water availability at ungaged stream locations in Massachusetts

Federal, State and local water-resource managers require a variety of data and modeling tools to better understand water resources. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a statewide, interactive decision-support tool to meet this need. The decision-support tool, referred to as the Massachusetts Sustainable-Yield Estimator (MA SYE) provides screening-level estimates of the sustainable yield of a basin, defined as the difference between the unregulated streamflow and some user-specified quantity of water that must remain in the stream to support such functions as recreational activities or aquatic habitat. The MA SYE tool was designed, in part, because the quantity of surface water available in a basin is a time-varying quantity subject to competing demands for water. To compute sustainable yield, the MA SYE tool estimates a daily time series of unregulated, daily mean streamflow for a 44-year period of record spanning October 1, 1960, through September 30, 2004. Selected streamflow quantiles from an unregulated, daily flow-duration curve are estimated by solving six regression equations that are a function of physical and climate basin characteristics at an ungaged site on a stream of interest. Streamflow is then interpolated between the estimated quantiles to obtain a continuous daily flow-duration curve. A time series of unregulated daily streamflow subsequently is created by transferring the timing of the daily streamflow at a reference streamgage to the ungaged site by equating exceedence probabilities of contemporaneous flow at the two locations. One of 66 reference streamgages is selected by kriging, a geostatistical method, which is used to map the spatial relation among correlations between the time series of the logarithm of daily streamflows at each reference streamgage and the ungaged site. Estimated unregulated, daily mean streamflows show good agreement with observed unregulated, daily mean streamflow at 18 streamgages located across southern New England. Nash-Sutcliffe efficiency goodness-of-fit values are between 0.69 and 0.98, and percent root-mean-square-error values are between 19 and 283 percent. The MA SYE tool provides an estimate of streamflow adjusted for current (2000-04) water withdrawals and discharges using a spatially referenced database of permitted groundwater and surface-water withdrawal and discharge volumes. For a user-selected basin, the database is queried to obtain the locations of water withdrawal or discharge volumes within the basin. Groundwater and surface-water withdrawals and discharges are subtracted and added, respectively, from the unregulated, daily streamflow at an ungaged site to obtain a streamflow time series that includes the effects of these withdrawals and discharges. Users also have the option of applying an analytical solution to the time-varying, groundwater withdrawal and discharge volumes that take into account the effects of the aquifer properties on the timing and magnitude of streamflow alteration. For the MA SYE tool, it is assumed that groundwater and surface-water divides are coincident. For areas of southeastern Massachusetts and Cape Cod where this assumption is known to be violated, groundwater-flow models are used to estimate average monthly streamflows at fixed locations. There are several limitations to the quality and quantity of the spatially referenced database of groundwater and surface-water withdrawals and discharges. The adjusted streamflow values do not account for the effects on streamflow of climate change, septic-system discharge, impervious area, non-public water-supply withdrawals less than 100,000 gallons per day, and impounded surface-water bodies.

Massachusetts

Scenarios of land use and land cover change in the conterminous United States: Utilizing the special report on emission scenarios at ecoregional scales

Global environmental change scenarios have typically provided projections of land use and land cover for a relatively small number of regions or using a relatively coarse resolution spatial grid, and for only a few major sectors. The coarseness of global projections, in both spatial and thematic dimensions, often limits their direct utility at scales useful for environmental management. This paper describes methods to downscale projections of land-use and land-cover change from the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios to ecological regions of the conterminous United States, using an integrated assessment model, land-use histories, and expert knowledge. Downscaled projections span a wide range of future potential conditions across sixteen land use/land cover sectors and 84 ecological regions, and are logically consistent with both historical measurements and SRES characteristics. Results appear to provide a credible solution for connecting regionalized projections of land use and land cover with existing downscaled climate scenarios, under a common set of scenario-based socioeconomic assumptions.

Global Environmental Change

Ecological risks of shale oil and gas development to wildlife, aquatic resources and their habitats

Technological advances in hydraulic fracturing and horizontal drilling have led to the exploration and exploitation of shale oil and gas both nationally and internationally. Extensive development of shale resources has occurred within the United States over the past decade, yet full build out is not expected to occur for years. Moreover, countries across the globe have large shale resources and are beginning to explore extraction of these resources. Extraction of shale resources is a multistep process that includes site identification, well pad and infrastructure development, well drilling, high-volume hydraulic fracturing and production; each with its own propensity to affect associated ecosystems. Some potential effects, for example from well pad, road and pipeline development, will likely be similar to other anthropogenic activities like conventional gas drilling, land clearing, exurban and agricultural development and surface mining (e.g., habitat fragmentation and sedimentation). Therefore, we can use the large body of literature available on the ecological effects of these activities to estimate potential effects from shale development on nearby ecosystems. However, other effects, such as accidental release of wastewaters, are novel to the shale gas extraction process making it harder to predict potential outcomes. Here, we review current knowledge of the effects of high-volume hydraulic fracturing coupled with horizontal drilling on terrestrial and aquatic ecosystems in the contiguous United States, an area that includes 20 shale plays many of which have experienced extensive development over the past decade. We conclude that species and habitats most at risk are ones where there is an extensive overlap between a species range or habitat type and one of the shale plays (leading to high vulnerability) coupled with intrinsic characteristics such as limited range, small population size, specialized habitat requirements, and high sensitivity to disturbance. Examples include core forest habitat and forest specialists, sagebrush habitat and specialists, vernal pond inhabitants and stream biota. We suggest five general areas of research and monitoring that could aid in development of effective guidelines and policies to minimize negative impacts and protect vulnerable species and ecosystems: (1) spatial analyses, (2) species-based modeling, (3) vulnerability assessments, (4) ecoregional assessments, and (5) threshold and toxicity evaluations.

Environmental Science & Technology

Adaptive management: The U.S. Department of the Interior technical guide

The purpose of this technical guide is to present an operational definition of adaptive management, identify the conditions in which adaptive management should be considered, and describe the process of using adaptive management for managing natural resources. The guide is not an exhaustive discussion of adaptive management, nor does it include detailed specifications for individual projects. However, it should aid U.S. Department of the Interior (DOI) managers and practitioners in determining when and how to apply adaptive management. Adaptive management is framed within the context of structured decision making, with an emphasis on uncertainty about resource responses to management actions and the value of reducing that uncertainty to improve management. Though learning plays a key role in adaptive management, it is seen here as a means to an end, namely good management, and not an end in itself. The operational definition used in the guide is adopted from the National Research Council, which characterizes adaptive management as an iterative learning process producing improved understanding and improved management over time: Adaptive management [is a decision process that] promotes flexible decision making that can be adjusted in the face of uncertainties as outcomes from management actions and other events become better understood. Careful monitoring of these outcomes both advances scientific understanding and helps adjust policies or operations as part of an iterative learning process. Adaptive management also recognizes the importance of natural variability in contributing to ecological resilience and productivity. It is not a ‘trial and error’ process, but rather emphasizes learning while doing. Adaptive management does not represent an end in itself, but rather a means to more effective decisions and enhanced benefits. Its true measure is in how well it helps meet environmental, social, and economic goals, increases scientific knowledge, and reduces tensions among stakeholders. Adaptive management as defined here involves ongoing, real-time learning and knowledge creation, both in a substantive sense and in terms of the adaptive process itself. It is described in what follows in a series of 9 steps, as summarized in section 4.1, involving stakeholder involvement, management objectives, management alternatives, predictive models, monitoring plans, decision making, monitoring responses to management, assessment, and adjustment to management actions. An adaptive approach actively engages stakeholders in all phases of a project over its timeframe, facilitating mutual learning and reinforcing the commitment to learning-based management. Adaptive management in DOI is implemented within a legal context that includes statutory authorities such as the National Environmental Policy Act (NEPA), the Endangered Species Act, and the Federal Advisory Committee Act. For many important problems now facing the resource management community, adaptive management holds great promise in reducing the uncertainties that limit the effective management of natural resource systems. For many conservation and management problems, utilizing management itself in an experimental context may be the only feasible way to gain the system understanding needed to improve management. Though it is commonly thought that an adaptive approach can produce results quickly at low cost, the opposite is more likely to be true. An initial investment of time and effort will increase the likelihood of better decision making and resource stewardship in the future, but patience, flexibility, and support are needed over the life of an adaptive management project. For these reasons it is important to carefully consider the potential use of an adaptive approach, and to engage in careful planning and evaluation when adaptive management is used.

Report

Modeling water quality in watersheds: From here to the next generation

In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in‐stream water quality and process interactions, soil health and land management, and (peri‐)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches, and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure, and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.

Water Resources Research

Molecular detection of hematozoa infections in tundra swans relative to migration patterns and ecological conditions at breeding grounds

Tundra swans ( Cygnus columbianus ) are broadly distributed in North America, use a wide variety of habitats, and exhibit diverse migration strategies. We investigated patterns of hematozoa infection in three populations of tundra swans that breed in Alaska using satellite tracking to infer host movement and molecular techniques to assess the prevalence and genetic diversity of parasites. We evaluated whether migratory patterns and environmental conditions at breeding areas explain the prevalence of blood parasites in migratory birds by contrasting the fit of competing models formulated in an occupancy modeling framework and calculating the detection probability of the top model using Akaike Information Criterion (AIC). We described genetic diversity of blood parasites in each population of swans by calculating the number of unique parasite haplotypes observed. Blood parasite infection was significantly different between populations of Alaska tundra swans, with the highest estimated prevalence occurring among birds occupying breeding areas with lower mean daily wind speeds and higher daily summer temperatures. Models including covariates of wind speed and temperature during summer months at breeding grounds better predicted hematozoa prevalence than those that included annual migration distance or duration. Genetic diversity of blood parasites in populations of tundra swans appeared to be relative to hematozoa prevalence. Our results suggest ecological conditions at breeding grounds may explain differences of hematozoa infection among populations of tundra swans that breed in Alaska.

Alaska

ERF1_2 -- Enhanced River Reach File 2.0

The digital segmented network based on watershed boundaries, ERF1_2, includes enhancements to the U.S. Environmental Protection Agency's River Reach File 1 (RF1) (USEPA, 1996; DeWald and others, 1985) to support national and regional-scale surface water-quality modeling. Alexander and others (1999) developed ERF1, which assessed the hydrologic integrity of the digital reach traces and calculated the mean water time-of-travel in river reaches and reservoirs. ERF1_2 serves as the foundation for SPARROW (Spatially Referenced Regressions (of nutrient transport) on Watershed) modeling. Within the context of a Geographic Information System, SPARROW estimates the proportion of watersheds in the conterminous U.S. with outflow concentrations of several nutrients, including total nitrogen and total phosphorus, (Smith, R.A., Schwarz, G.E., and Alexander, R.B., 1997). This version of the network expands on ERF1 (Version 1.2; Alexander, et al., 1999) and includes the incremental and total drainage area derived from 1-kilometer (km) elevation data for North America. Previous estimates of the water time-of-travel were recomputed for reaches with water-quality monitoring sites that included two reaches. The mean flow and velocity estimates for these split reaches are based on previous estimation methods (Alexander et al., 1999) and are unchanged in ERF1_2. Drainage area calculations provide data used to estimate the contribution of a given nutrient to the outflow. Data estimates depend on the accuracy of node connectivity. Reaches split at water-quality or pesticide-monitoring sites indicate the source point for estimating the contribution and transport of nutrients and their loads throughout the watersheds. The ERF1_2 coverage extends the earlier drainage area founded on the 1-kilometer data for North America (Verdin, 1996; Verdin and Jenson, 1996). A 1-kilometer raster grid of ERF1_2 projected to Lambert Azimuthal Equal Area, NAD 27 Datum (Snyder, 1987), was merged with the HYDRO1K flow direction data set (Verdin and Jenson, 1996) to generate a DEM-based watershed grid, ERF1_2WS_LG. The watershed boundaries are maintained in a raster (grid cell) format as well as a vector (polygon) format for subsequent model analysis. Both the coverage, ERF1_2, and the grid, ERF1_2WS_LG, are available at: URL:http://water.usgs.gov/lookup/getspatial?erf1_2

Open-File Report

Collaborative decision-analytic framework to maximize resilience of tidal marshes to climate change

Decision makers that are responsible for stewardship of natural resources face many challenges, which are complicated by uncertainty about impacts from climate change, expanding human development, and intensifying land uses. A systematic process for evaluating the social and ecological risks, trade-offs, and cobenefits associated with future changes is critical to maximize resilience and conserve ecosystem services. This is particularly true in coastal areas where human populations and landscape conversion are increasing, and where intensifying storms and sea-level rise pose unprecedented threats to coastal ecosystems. We applied collaborative decision analysis with a diverse team of stakeholders who preserve, manage, or restore tidal marshes across the San Francisco Bay estuary, California, USA, as a case study. Specifically, we followed a structured decision-making approach, and we using expert judgment developed alternative management strategies to increase the capacity and adaptability to manage tidal marsh resilience while considering uncertainties through 2050. Because sea-level rise projections are relatively confident to 2050, we focused on uncertainties regarding intensity and frequency of storms and funding. Elicitation methods allowed us to make predictions in the absence of fully compatible models and to assess short- and long-term trade-offs. Specifically we addressed two questions. (1) Can collaborative decision analysis lead to consensus among a diverse set of decision makers responsible for environmental stewardship and faced with uncertainties about climate change, funding, and stakeholder values? (2) What is an optimal strategy for the conservation of tidal marshes, and what strategy is robust to the aforementioned uncertainties? We found that when taking this approach, consensus was reached among the stakeholders about the best management strategies to maintain tidal marsh integrity. A Bayesian decision network revealed that a strategy considering sea-level rise and storms explicitly in wetland restoration planning and designs was optimal, and it was robust to uncertainties about management effectiveness and budgets. We found that strategies that avoided explicitly accounting for future climate change had the lowest expected performance based on input from the team. Our decision-analytic framework is sufficiently general to offer an adaptable template, which can be modified for use in other areas that include a diverse and engaged stakeholder group.

California

Feedback of land subsidence on the movement and conjunctive use of water resources

The dependency of surface- or groundwater flows and aquifer hydraulic properties on dewatering-induced layer deformation is not available in the USGS's groundwater model MODFLOW. A new integrated hydrologic model, MODFLOW-OWHM, formulates this dependency by coupling mesh deformation with aquifer transmissivity and storage and by linking land subsidence/uplift with deformation-dependent flows that also depend on aquifer head and other flow terms. In a test example, flows most affected were stream seepage and evapotranspiration from groundwater (ET gw ). Deformation feedback also had an indirect effect on conjunctive surface- and groundwater use components: Changed stream seepage and streamflows influenced surface-water deliveries and returnflows. Changed ET gw affected irrigation demand, which jointly with altered surface-water supplies resulted in changed supplemental groundwater requirements and pumping and changed return runoff. This modeling feature will improve the impact assessment of dewatering-induced land subsidence/uplift (following irrigation pumping or coal-seam gas extraction) on surface receptors, inter-basin transfers, and surface-infrastructure integrity.

Environmental Modelling and Software

The role of stand history in assessing forest impacts

Air pollution, harvesting practices, and natural disturbances can affect the growth of trees and forest development. To make predictions about anthropogenic impacts on forests, we need to understand how these factors affect tree growth. In this study the effect of disturbance history on tree growth and stand structure was examined by using a computer model of forest development. The model was run under the climatic conditions of east Tennessee, USA, and the results compared to stand structure and tree growth data from a yellow poplar-white oak forest. Basal area growth and forest biomass were more accurately projected when rough approximations of the thinning and fire history typical of the measured plots were included in the simulation model. Stand history can influence tree growth rates and forest structure and should be included in any attempt to assess forest impacts.

Environmental Management

A stakeholder project to model water temperature under future climate scenarios in the Satus and Toppenish watersheds of the Yakima River Basinin Washington, USA

The goal of this study was to support an assessment of the potential effects of climate change on select natural, social, and economic resources in the Yakima River Basin. A workshop with local stakeholders highlighted the usefulness of projecting climate change impacts on anadromous steelhead ( Oncorhynchus mykiss) , a fish species of importance to local tribes, fisherman, and conservationists. Stream temperature is an important environmental variable for the freshwater stages of steelhead. For this study, we developed water temperature models for the Satus and Toppenish watersheds, two of the key stronghold areas for steelhead in the Yakima River Basin. We constructed the models with the Stream Network Temperature Model (SNTEMP), a mechanistic approach to simulate water temperature in a stream network. The models were calibrated over the April 15, 2008 to September 30, 2008 period and validated over the April 15, 2009 to September 30, 2009 period using historic measurements of stream temperature and discharge provided by the Yakama Nation Fisheries Resource Management Program. Once validated, the models were run to simulate conditions during the spring and summer seasons over a baseline period (1981–2005) and two future climate scenarios with increased air temperature of 1°C and 2°C. The models simulated daily mean and maximum water temperatures at sites throughout the two watersheds under the baseline and future climate scenarios.

Washington

An integrated model of environmental effects on growth, carbohydrate balance, and mortality of Pinus ponderosa forests in the southern Rocky Mountains

Climate-induced tree mortality is an increasing concern for forest managers around the world. We used a coupled hydrologic and ecosystem carbon cycling model to assess temperature and precipitation impacts on productivity and survival of ponderosa pine ( Pinus ponderosa ). Model predictions were evaluated using observations of productivity and survival for three ponderosa pine stands located across an 800 m elevation gradient in the southern Rocky Mountains, USA, during a 10-year period that ended in a severe drought and extensive tree mortality at the lowest elevation site. We demonstrate the utility of a relatively simple representation of declines in non-structural carbohydrate (NSC) as an approach for estimating patterns of ponderosa pine vulnerability to drought and the likelihood of survival along an elevation gradient. We assess the sensitivity of simulated net primary production, NSC storage dynamics, and mortality to site climate and soil characteristics as well as uncertainty in the allocation of carbon to the NSC pool. For a fairly wide set of assumptions, the model estimates captured elevational gradients and temporal patterns in growth and biomass. Model results that best predict mortality risk also yield productivity, leaf area, and biomass estimates that are qualitatively consistent with observations across the sites. Using this constrained set of parameters, we found that productivity and likelihood of survival were equally dependent on elevation-driven variation in temperature and precipitation. Our results demonstrate the potential for a coupled hydrology-ecosystem carbon cycling model that includes a simple model of NSC dynamics to predict drought-related mortality. Given that increases in temperature and in the frequency and severity of drought are predicted for a broad range of ponderosa pine and other western North America conifer forest habitats, the model potentially has broad utility for assessing ecosystem vulnerabilities.

Jemez Mountains, Rocky Mountains