Penumbra : A Spatiotemporal Shade-Irradiance Analysis Tool with External Model Integration for Landscape Assessment, Habitat Enhancement, and Water Quality Improvement

Several solar energy models exist, but all models must balance: computational runtime, light complexity, and model output volume. These models span the spectrum of simplistic global solar energy equation sets to complex light ray-tracing models. Spatiotemporally inaccurate representations of solar energy may cause compounding simulation effects and introduce unknown modeling uncertainty. Within the current solar energy modeling spectrum was the need to advance large watershed area spatiotemporal irradiance modeling. A model utilizing methods simpler than ray-tracing that still accounted for the major environmental light reduction factors was needed. The model developed we called Penumbra. Penumbra provides solar energy reduction from topographic shadowing, forest shadowing, and cloud coverage at landscape scales. Penumbra was developed to function as a stand-alone model, but also be capable of integration within existing ecosystem models. Penumbra’s intended audience include ecosystem modelers, land owners, watershed councils, county, state, and federal entities; any group needing an enhanced understanding of how light energy impacts processes within their landscapes. The questions being asked by my intended audience regard riparian zone restoration, fish habitat restoration, and improved forest management. To address these questions, a well-functioning shade|irradiance model capable of assisting with multiyear landscape assessments was needed

An integrated environmental and human systems modeling framework for Puget Sound restoration planning

Local, state, federal, tribal and private stakeholders have committed significant resources to restoring Puget Sound’s terrestrial-marine ecosystem. Though jurisdictional issues have promoted a fragmented approach to restoration planning, there is growing recognition that a more coordinated systems-based restoration approach is needed to achieve recovery goals. This presentation describes our collaborative effort to develop and apply an integrated environmental and human systems modeling framework for the Puget Sound Basin, inclusive of all marine and land areas (1,020 and 12,680 sq. mi.). Our goal is to establish a whole-basin systems modeling framework that dynamically simulates biophysical interactions and transfers (water, nutrients, contaminants, biota) across terrestrial-marine boundaries. The core environmental models include a terrestrial ecohydrological model (VELMA), an ocean circulation and biogeochemistry model (Salish Sea Model), and an ocean food web model (Atlantis). This environmental subsystem will be linked with an agent-based modeling subsystem (e.g., Envision) that allows human decision-makers to be represented in whole-basin simulations. The integrated environmental and human systems framework aims to facilitate discourse among different stakeholders and decision makers (agents) and enable them play out the ecological, social and economic consequences of alternative ecosystem restoration choices. All of these models are currently being applied in Puget Sound, but they have not yet been integrated. The linked models will better capture the propagation of human impacts throughout the terrestrial-marine ecosystem, and thereby provide a more effective decision support tool for addressing restoration of high priority environmental endpoints, such as the Vital Signs identified by the Puget Sound Partnership (http://www.psp.wa.gov/vitalsigns/). Our overview will include examples of existing stand-alone model applications, and conceptual plans for linking models across terrestrial-marine boundaries. The Puget Sound multi-model framework described here can potentially be expanded to address the entire Salish Sea transboundary ecosystem (https://www.eopugetsound.org/maps/salish-sea-basin-and-water-boundaries)

Quantifying ecosystem service tradeoffs in response to alternative land use and climate scenarios: Pacific Northwest applications of the VELMA ecohydrological model

Scientists, policymakers, community planners and others have discussed ecosystem services for decades, however, society is still in the early stages of developing methodologies to quantify and value the goods and services that ecosystems provide. Essential to this goal are highly integrated models that can be used to define policy and management strategies for entire ecosystems, not just individual components. We developed the VELMA ecohydrological model to help address this need. VELMA links a land surface hydrologic model with a terrestrial biogeochemistry model in a spatially-distributed framework to simulate the integrated responses of vegetation, soil, and water resources to changes in land use and climate. Here we briefly describe watershed-scale applications of VELMA conducted in Oregon and the Puget Sound Basin in partnership with community and governmental organizations. Our goal is to evaluate how alternative policy, land use and climate scenarios affect tradeoffs among ecosystem services – specifically, provisioning services (water; food from land and sea; fiber), supporting services (cycling of water and nutrients; habitat for fish, shellfish, wildlife), regulating services (climate; peak and low flows), and cultural services (recreational and spiritual pursuits). A major focus is to assess the effectiveness of natural and engineered green infrastructure (riparian buffers etc.) for protecting water quality of coastal and inland waters. Products of this work include (1) alternative-future scenarios capturing stakeholder-relevant choices and drivers of change; (2) tools for mapping production of ecosystem goods and services under current and projected conditions; and (3) tools for evaluating ecosystem service tradeoffs so that natural capital can be more fully accounted for in alternative-future decision scenarios. We are using these products in a participatory planning approach that integrates researchers, stakeholders and decision makers in the process of identifying drivers, ecosystem services of concern, and solutions for a more sustainable future. For example, can optimal “decision paths” be identified for restoring the ecosystem services needed to sustainably support communities dependent on resource-based economies and traditions, such as agriculture, forestry, and fishing

Urban watershed modeling in Seattle, Washington using VELMA: a spatially explicit ecohydrological watershed model

Urban watersheds are notoriously difficult to model due to their complex, small-scale combinations of landscape and land use characteristics including impervious surfaces that ultimately affect the hydrologic system. We utilized EPA’s Visualizing Ecosystem Land Management Assessments (VELMA) model, which is a spatially explicit (i.e., gridded) ecohydrological watershed model, to simulate watershed-scale hydrologic discharge and nutrient concentrations for several urban stream systems in Seattle, Washington, including Thornton Creek, Piper’s Creek, Longfellow Creek, and Taylor Creek. A 1-meter land use classification is used to distinguish four cover types, including roads, buildings, trees, and grass. After model calibration and validation, we construct scenarios of hypothetical green roof implementations and simulate their impacts on watershed-scale discharge. Results show that VELMA is capable of simulating the impacts of targeted green infrastructure management practices to reduce peak stream flow events. These results suggest that VELMA can facilitate the prioritization of urban water infrastructure to improve water quality in urban streams leading to Puget Sound

Penumbra: A spatially distributed, mechanistic model for simulating ground-level incident solar energy across heterogeneous landscapes.

Landscape solar energy is a significant environmental driver, yet it remains complicated to model well. Several solar radiation models simplify the complexity of light by estimating it at discrete point locations or by averaging values over larger areas. These modeling approaches may be useful in certain cases, but they are unable to provide spatially distributed and temporally dynamic representations of solar energy across entire landscapes. We created a landscape-scale ground-level shade and solar energy model called Penumbra to address this deficiency. Penumbra simulates spatially distributed ground-level shade and incident solar energy at user-defined timescales by modeling local and distant topographic shading and vegetative shading. Spatially resolved inputs of a digital elevation model, a normalized digital surface model, and landscape object transmittance are used to estimate spatial variations in solar energy at user-defined temporal timesteps. The research goals for Penumbra included: 1) simulations of spatiotemporal variations of shade and solar energy caused by both objects and topographic features, 2) minimal user burden and parameterization, 3) flexible user defined temporal parameters, and 4) flexible external model coupling. We test Penumbra's predictive skill by comparing the model's predictions with monitored open and forested sites, and achieve calibrated mean errors ranging from -17.3 to 148.1 μmoles/m2/s. Penumbra is a dynamic model that can produce spatial and temporal representations of shade percentage and ground-level solar energy. Outputs from Penumbra can be used with other ecological models to better understand the health and resilience of aquatic, near stream terrestrial, and upland ecosystems

Improved Soil Temperature Modeling Using Spatially Explicit Solar Energy Drivers

Modeling the spatial and temporal dynamics of soil temperature is deterministically complex due to the wide variability of several influential environmental variables, including soil column composition, soil moisture, air temperature, and solar energy. Landscape incident solar radiation is a significant environmental driver that affects both air temperature and ground-level soil energy loading; therefore, inclusion of solar energy is important for generating accurate representations of soil temperature. We used the U.S. Environmental Protection Agency’s Oregon Crest-to-Coast (O’CCMoN) Environmental Monitoring Transect dataset to develop and test the inclusion of ground-level solar energy driver data within an existing soil temperature model currently utilized within an ecohydrology model called Visualizing Ecosystem Land Management Assessments (VELMA). The O’CCMoN site data elucidate how localized ground-level solar energy between open and forested landscapes greatly influence the resulting soil temperature. We demonstrate how the inclusion of local ground-level solar energy significantly improves the ability to deterministically model soil temperature at two depths. These results suggest that landscape and watershed-scale models should incorporate spatially distributed solar energy to improve spatial and temporal simulations of soil temperature

Tough places and safe spaces: Can refuges save salmon from a warming climate?

Abstract The importance of thermal refuges in a rapidly warming world is particularly evident for migratory species, where individuals encounter a wide range of conditions throughout their lives. In this study, we used a spatially explicit, individual‐based simulation model to evaluate the buffering potential of cold‐water thermal refuges for anadromous salmon and trout (Oncorhynchus spp.) migrating upstream through a warm river corridor that can expose individuals to physiologically stressful temperatures. We considered upstream migration in relation to migratory phenotypes that were defined in terms of migration timing, spawn timing, swim speed, and use of cold‐water thermal refuges. Individuals with different migratory phenotypes migrated upstream through riverine corridors with variable availability of cold‐water thermal refuges and mainstem temperatures. Use of cold‐water refuges (CWRs) decreased accumulated sublethal exposures to physiologically stressful temperatures when measured in degree‐days above 20, 21, and 22°C. The availability of CWRs was an order of magnitude more effective in lowering accumulated sublethal exposures under current and future mainstem temperatures for summer steelhead than fall Chinook Salmon. We considered two emergent model outcomes, survival and percent of available energy used, in relation to thermal heterogeneity and migratory phenotype. Mean percent energy loss attributed to future warmer mainstem temperatures was at least two times larger than the difference in energy used in simulations without CWRs for steelhead and salmon. We also found that loss of CWRs reduced the diversity of energy‐conserving migratory phenotypes when we examined the variability in entry timing and travel time outside of CWRs in relation to energy loss. Energy‐conserving phenotypic space contracted by 7%–23% when CWRs were unavailable under the current thermal regime. Our simulations suggest that, while CWRs do not entirely mitigate for stressful thermal exposures in mainstem rivers, these features are important for maintaining a diversity of migration phenotypes. Our study suggests that the maintenance of diverse portfolios of migratory phenotypes and cool‐ and cold‐water refuges might be added to the suite of policies and management actions presently being deployed to improve the likelihood of Pacific salmonid persistence into a future characterized by climate change

Integrated decision support tools for Puget Sound salmon recovery planning

We developed a set of tools to provide decision support for community-based salmon recovery planning in Salish Sea watersheds. Here we describe how these tools are being integrated and applied in collaboration with Puget Sound tribes and community stakeholders to address restoration of hydrological and ecological processes critical to salmon recovery, and more broadly, to the functioning of entire watersheds and the ecosystem services they provide. For ongoing case studies in the Nisqually River and Tolt River watersheds in Washington, we are using a spatially-distributed watershed simulator – VELMA (Visualizing Ecosystem Land Management Assessments) – to quantify long-term effects of alternative forest management and climate scenarios on key salmon habitat variables, including peak and low flows, in-stream wood, fine sediment in spawning beds, and riparian condition. Stream temperature will be simulated using Penumbra, a new stream shade and temperature model that is being integrated with VELMA. VELMA/Penumbra stream habitat outputs will be used to drive the EDT (Ecosystem Diagnosis and Treatment) fish habitat model to simulate habitat potential and salmon population responses to the forest management and climate scenarios. A 3-D visualization tool (VISTAS; Cushing et al. 2009) is being used to summarize and communicate model outcomes in an intuitive way. An important goal of the case studies is to identify community-based best management practices for mitigating and adapting to projected changes in climate. For example, where and what kinds of in-stream, riparian and upland restoration practices will be most effective for improving cold water refuges, spawning and rearing habitat, and hydrologic flow regimes (higher summer flows and lower peak flows)? Model results are also being used to help address other community concerns, such as the establishment of a Nisqually Community Forest that sustainably supports forest-sector jobs, recreation and tourism

NKp30 isoforms and NKp30 ligands are predictive biomarkers of response to imatinib mesylate in metastatic GIST patients

Despite effective targeted therapy acting on KIT and PDGFRA tyrosine kinases, gastrointestinal stromal tumors (GIST) escape treatment by acquiring mutations conveying resistance to imatinib mesylate (IM). Following the identification of NKp30-based immunosurveillance of GIST and the off-target effects of IM on NK cell functions, we investigated the predictive value of NKp30 isoforms and NKp30 soluble ligands in blood for the clinical response to IM. The relative expression and the proportions of NKp30 isoforms markedly impacted both event-free and overall survival, in two independent cohorts of metastatic GIST. Phenotypes based on disbalanced NKp30B/NKp30C ratio (Delta BClow) and low expression levels of NKp30A were identified in one third of patients with dismal prognosis across molecular subtypes. This Delta BClow blood phenotype was associated with a pro-inflammatory and immunosuppressive tumor microenvironment. In addition, detectable levels of the NKp30 ligand sB7-H6 predicted a worse prognosis in metastatic GIST. Soluble BAG6, an alternate ligand for NKp30 was associated with low NKp30 transcription and had additional predictive value in GIST patients with high NKp30 expression. Such GIST microenvironments could be rescued by therapy based on rIFN-alpha and anti-TRAIL mAb which reinstated innate immunity