Downscaling global ocean climate models improves estimates of exposure regimes in coastal environments

Nature Portfolio (Springer Nature) | August 26th, 2020

Climate change is expected to warm, deoxygenate, and acidify ocean waters. Global climate models (GCMs) predict future conditions at large spatial scales, and these pred

Climate change is expected to warm, deoxygenate, and acidify ocean waters. Global climate models (GCMs) predict future conditions at large spatial scales, and these predictions are then often used to parameterize laboratory experiments designed to assess biological and ecological responses to future change. However, nearshore ecosystems are affected by a range of physical processes such as tides, local winds, and surface and internal waves, causing local variability in conditions that often exceeds global climate models. Predictions of future climatic conditions at local scales, the most relevant to ecological responses, are largely lacking. To fill this critical gap, we developed a 2D implementation of the Regional Ocean Modeling System (ROMS) to downscale global climate predictions across all Representative Concentration Pathway (RCP) scenarios to smaller spatial scales, in this case the scale of a temperate reef in the northeastern Pacific. To assess the potential biological impacts of local climate variability, we then used the results from different climate scenarios to estimate how climate change may affect the survival, growth, and fertilization of a representative marine benthic invertebrate, the red abalone Haliotis rufescens, to a highly varying multi-stressor environment. We found that high frequency variability in temperature, dissolved oxygen (DO), and pH increases as pCO2 increases in the atmosphere. Extreme temperature and pH conditions are generally not expected until RCP 4.5 or greater, while frequent exposure to low DO is already occurring. In the nearshore environment simulation, strong RCP scenarios can affect red abalone growth as well as reduce fertilization during extreme conditions when compared to global scale simulations.

DRAFT Staff Report/Substitute Environmental Document in Support of Potential Updates to the Water Quality Control Plan for the San Francisco Bay/Sacramento-San Joaquin Delta Estuary for the Sacramento River and its Tributaries, Delta Eastside Tributaries, and Delta

California State Water Resources Control Board (SWRCB) | September 28th, 2023

Dramatic declines in snowpack in the western US

Nature Portfolio (Springer Nature) | March 2nd, 2018

Mountain snowpack stores a significant quantity of water in the western US, accumulating during the wet season and melting during the dry summers and supplying

Mountain snowpack stores a significant quantity of water in the western US, accumulating during the wet season and melting during the dry summers and supplying much of the water used for irrigated agriculture, and municipal and industrial uses. Updating our earlier work published in 2005, we find that with 14 additional years of data, over 90% of snow monitoring sites with long records across the western US now show declines, of which 33% are significant (vs. 5% expected by chance) and 2% are significant and positive (vs. 5% expected by chance). Declining trends are observed across all months, states, and climates, but are largest in spring, in the Pacific states, and in locations with mild winter climate. We corroborate and extend these observations using a gridded hydrology model, which also allows a robust estimate of total western snowpack and its decline. We find a large increase in the fraction of locations that posted decreasing trends, and averaged across the western US, the decline in average April 1 snow water equivalent since mid-century is roughly 15–30% or 25–50 km3, comparable in volume to the West’s largest man-made reservoir, Lake Mead.

DRERIP Ecosystem Conceptual Model: Chemical stressors

California Department of Fish and Wildlife (CDFW) | February 5th, 2008

The Sacramento-San Joaquin Delta ecosystem comprises many different habitat types, and is home to a large number of species. Thousands of chemical contaminants have been

The Sacramento-San Joaquin Delta ecosystem comprises many different habitat types, and is home to a large number of species. Thousands of chemical contaminants have been or are being introduced into the Delta. The conceptual model presented here is therefore general in nature, and is intended to provide a framework for more refined models for individual species, habitats and, in particular, contaminants of interest, for example selenium, mercury and pyrethroids. The model consists of three major submodels (Figure 1). Submodel 1: Exposure assessment which includes fate and transport of contaminants and the co-occurrence of chemicals with Delta organisms; the intermediate outcome of this submodel is “Exposure Concentration”. Submodel 2: Bioavailability of contaminants to Delta organisms; the intermediate outcome of this submodel is “Bioavailable Concentration” or “Dose”.  Submodel 3: Toxic effects assessment with the final model outcome “Population Level Effects”. In the following narrative, we provide a description for each submodel, its parameters, and linkages to other models. We discuss the model’s limitations and provide recommendations for its application in management.

DRERIP Ecosystem Conceptual Model: Chinook Salmon & Steelhead

California Department of Fish and Wildlife (CDFW) | September 4th, 2012

This report constitutes the conceptual model for Chinook and steelhead for the Delta Regional Ecosystem Restoration Implementation Plan (DRERIP). The report describes

This report constitutes the conceptual model for Chinook and steelhead for the Delta Regional Ecosystem Restoration Implementation Plan (DRERIP). The report describes conceptual models, not numerical models, but several important considerations apply to both kinds, especially when they are used for management of living natural resources. First, the proper purpose of models is to help people think, not to think for them. Ignoring this can be disastrous, as exemplified by the current economic crisis. The world of credit default swaps was built on highly sophisticated models that persuaded many intelligent people that the associated risk was negligible, but they failed to recognize that a market based on houses that people could not pay for from their earnings is unsustainable. In short, the most important output of a good conceptual or numerical model is clear thinking. To help people think, the model must be focused on selected features of the world that are thought to be important for the purpose at hand: in this case, management of the Delta. A model that tries to include everything will be too complex to be useful for this purpose. Second, to be useful for management of natural living resources, numerical models must be unrealistic, because our knowledge of such resources is incomplete, and is based on data that includes measurement errors. According to Ludwig‘s paradox, "Effective management models cannot be realistic" (Ludwig 1994:516), because two kinds of uncertainty must be balanced (Figure I-1; see Ch. 14 in Williams (2006) for elaboration of this point). In our view, something similar applies to conceptual models of natural systems: to be useful, they must be simple. A schematic of the wiring in some electronic device is a conceptual model that may be useful as well as complex, but trying to develop a similar schematic of an ecosystem or part of an ecosystem is not useful, because our knowledge of such a system is much less complete than our knowledge of engineered devices, and we have only estimates of the relevant parameters. Finally, reality is too complex to capture with a single model. Eric Lander, a noted geneticist who co-chairs President Obama‘s Council of Advisors on Science and Technology, recently remarked that "You can never capture something like an economy, a genome or an ecosystem with one model or one taxonomy – it all depends on the questions you want to ask." (NY Times, 11/11/08). Models are tools that we use to try to think, and multi-purpose tools generally do nothing well. Therefore, although the complete life cycle of Chinook and steelhead is described here, the parts or aspects of the cycle that we think may be affected by management of the Delta are emphasized, and we try to keep it as simple as possible. More detail on most of the topics described here can be found in Quinn (2005), or in Williams (2006), from which this document draws very heavily.

DRERIP Ecosystem Conceptual Model: Delta Aquatic Foodweb

California Department of Fish and Wildlife (CDFW) | October 3rd, 2008

This model is a stylization of the actual food web dynamics of the Sacramento-San Joaquin Delta, which are highly dynamic. The region itself comprises a variety of habita

This model is a stylization of the actual food web dynamics of the Sacramento-San Joaquin Delta, which are highly dynamic. The region itself comprises a variety of habitats, determined by salinity regimes, residence time, hydrology, benthos and physical structure. These physical parameters, or drivers, determine species composition and trophic relationships. The Delta is a tidal system which is subject to varying water inflow. Because inflow and outflow vary as the result of anthropogenic alterations and water management needs, habitats are not static. Rather they are subject to hourly, daily, seasonal and inter-annual variation, and different organisms respond in different ways to these time scales, depending upon their own life histories. Thus salinity and temperature regimes may create different outcomes from food web interactions, based upon how species distributional and recruitment patterns overlap. In general, food web linkages are not static or linear. Organisms switch feeding strategies opportunistically, and these patterns of variability in feeding strategy tend to increase with trophic level. Many organisms, particularly plankton, undergo many generations in the course of a year, and selective forces may allow for rapid evolution which can alter habitat preferences or other life history characteristics. The Delta food web is further dynamic in that new species are regularly introduced into the Estuary, competing with, replacing, or preying upon other organisms. For example, the overbite clam, Corbula amurensis, was introduced in 1986, precipitating a cascade of changes that are still not wholly understood. Zebra and quagga mussels are expected to invade the Delta within the next few years, and will bring further changes. The topology of a food web model will be necessarily complex given these factors. Even without such variability, the potential linkages create a spider web of relationships that is difficult if not impossible to disentangle. In order to create a working model of the Delta food web that is useful for education, for hypothesis?generation, and for management decision?making, it is necessary to create limits to what linkages will be examined. In order to do this, this Delta food web model focuses on organisms that supply food for fish. This is particularly important given the recent concern for pelagic organism decline, which is described mostly for fishes, some of which are listed as endangered or threatened. A key assumption is that fish are integrators of ecosystem function. Also included in the model are invasive organisms that have a large impact on food web dynamics (such as C. amurensis), as are organisms that are particularly abundant (such as the copepod Limnoithona tetraspina), whether or not they are used directly by fish.

DRERIP Ecosystem Conceptual Model: Delta smelt

California Department of Fish and Wildlife (CDFW) | October 22nd, 2010

This Conceptual Model is part of a suite of conceptual models which collectively articulate the current scientific understanding of important aspects of the Sacramento-Sa

This Conceptual Model is part of a suite of conceptual models which collectively articulate the current scientific understanding of important aspects of the Sacramento-San Joaquin River Delta ecosystem. The conceptual models are designed to aid in the identification and evaluation of ecosystem restoration actions in the Delta. These models are designed to structure scientific information such that it can be used to inform sound public policy. The Delta Conceptual Models include both ecosystem element models (including process, habitat, and stressor models) and species life history models. The models were prepared by teams of experts using common guidance documents developed to promote consistency in the format and terminology of the models http://www.delta.dfg.ca.gov/erpdeltaplan/science_process.asp . The Delta Conceptual Models are qualitative models which describe current understanding of how the system works. They are designed and intended to be used by experts to identify and evaluate potential restoration actions. They are not quantitative, numeric computer models that can be “run” to determine the effects of actions. Rather they are designed to facilitate informed discussions regarding expected outcomes resulting from restoration actions and the scientific basis for those expectations. The structure of many of the Delta Conceptual Models can serve as the basis for future development of quantitative models.

DRERIP Ecosystem Conceptual Model: Fish Habitat Linkages

California Department of Fish and Wildlife (CDFW) | January 19th, 2008

The Delta Regional Ecosystem Restoration Implementation Plan (DRERIP) is one of four regional plans intended to guide the implementation of the CALFED Ecosystem Restorati

The Delta Regional Ecosystem Restoration Implementation Plan (DRERIP) is one of four regional plans intended to guide the implementation of the CALFED Ecosystem Restoration Program (ERP) element. The DRERIP will refine the planning foundation for the Delta, develop and refine specific restoration actions and provide project implementation guidance, program tracking, performance evaluation and adaptive management feedback specific to the Delta. The DRERIP Fish Habitat Linkage Model (FHL model) provides a roadmap for how the various conceptual models designed for the DRERIP process intertwine to define fish habitat and ultimately produce fish. The model identifies the key linkages between hydrology and numerous other components of fish habitat. The FHL model shows that hydrodynamics and water operations exert influences on fish recruitment by directly influencing transport fates, the water quality components of habitat, and some biotic interactions. The water quality components of habitat interact with structural components of habitat; their interaction affects the strength of biotic interactions (Peterson 2003). Because the FHL model is a generalized model serving as a template or road map, the relative importance of drivers and linkages, and their direction of impact (positive or negative), are not shown in the model diagram because they will depend on which species, contingent (sensu Secor 1999), or life stage is being evaluated. Additional general descriptions of the state of knowledge about these linkages are provided in the text boxes for each model component.

DRERIP Ecosystem Conceptual Model: Floodplain

California Department of Fish and Wildlife (CDFW) | January 22nd, 2008

Elements common to all models (Figure 1). Gray shapes (“plaques” in Word parlance) are other DRERIP models. Brown polygons are modifying factors. Pink rectangles are

Elements common to all models (Figure 1). Gray shapes (“plaques” in Word parlance) are other DRERIP models. Brown polygons are modifying factors. Pink rectangles are primary outputs of direct interest to Delta restoration planners (e.g., splittail). Blue rectangles are hydrological characteristics or variables, primarily pertaining to the primary river that is the source of inundation to the floodplain of interest but some rectangles represent “secondary hydrology” such as water deriving from direction precipitation on the floodplain, and groundwater and tributary inputs. Blue-green rectangles represent inundated habitat characteristics – properties of the floodplain during periods of inundation. Model 1 (Creating the Template) captures the linkages and processes that create the habitat mosaic—the physical template of a given floodplain, such as topography and vegetative communities (Figure 2). Note that habitat mosaic is more than vegetative communities as it also includes topographic features like side channels, oxbows, and wetlands. This is a very basic model, so we didn’t attempt to use the information-coded arrows to indicate importance, predictability, etc. This model describes how floodplain topography and vegetation, important features treated as more or less static in the other models, are created and maintained. This model encompasses time scales ranging from a single flood event (e.g., bank erosion) to decades or centuries (successional processes in a floodplain forest). Delta restoration planners can use model 1 to understand management options for creating and maintaining habitat mosaics on a given floodplain. Model 2 (Inundating the template) depicts how a given floodplain, with topography and vegetation created within Model 1, is inundated by river flows and other sources of water to create specific conditions within the inundated floodplain that are important to the species or processes described in model set 3 (Figure 3). The hydrology first encounters river-floodplain topography (e.g., the relative elevations of floodplain to river stage) to determine if the floodplain becomes inundated; the other linkages only occur if flow magnitude is capable of exceeding the inundation threshold. Inundation is a function of flow magnitude in the river, along with contributions from other hydrological sources (e.g., local tributaries, high water table), and the relative elevation and connectivity of the river-floodplain topography. If inundation occurs, the floodwaters interact with the topography and vegetation created in Model 1. As inundation occurs across this mosaic it results in a variety of inundated habitat characteristics—conditions that directly affect biota and processes during the period of inundation. These inundated habitat characteristics are the primary inputs for Model Set 3. This model is primarily focused at the temporal scale of a single flood season. Delta restoration planners can use model 2 to evaluate how management actions can influence the inundation of floodplain habitat mosaics and characteristics of the inundated habitat. Model Set 3 (Management outputs) illustrates how the inundated habitat characteristics, developed in Model 2, interact with a few other key elements to influence the production of biota of direct interest to delta restoration planners, including algae, zooplankton, splittail, and juvenile Chinook salmon (Figures 4 - 7). Model Set 3 encompasses a temporal scale of a single flood season. Model Set 3 can be used to evaluate how specific characteristics of the inundated floodplain affect specific outputs of management interest. Figure 4 provides a basic overview of the inputs and outputs and relationships between the models in Model Set 3. Figure 5 focuses on the production of algae (phytoplankton and epibenthic algae) and zooplankton, structured as a food web. Figures 6 and 7 show how the inundated habitat characteristics and base of the food web (algae and zooplankton) affect the production of splittail and Chinook salmon, respectively. Primary management outputs from floodplain models: 1. Primary productivity, in terms of phytoplankton, the most nutritious organic matter for the downstream delta (Muller-Solger et al. 2002) and secondary productivity (zooplankton and macroinvertebrates). Because several important species in the delta are food-limited, as indicated by low first-year survival, floodplain restoration has been promoted as a means of increasing productivity to these species and ecosystems (Jassby and Cloern 2000). 2. Juvenile Chinook 3. Splittail 4. Habitat mosaic and riparian structure for a variety of species. The first three management outputs are Model 3 outputs. For these a user can work backwards through the models to understand how management options can increase the productivity of a specific desired output. For example, if the desired output is biologically available Carbon for downstream ecosystems (algae), then Figure 5 (Model 3) indicates that residence time and intra-annual frequency are important characteristics; for these characteristics of inundation to occur, Figure 3 (Model 2) indicates that the frequency of inundation can be influenced either through hydrologic or topographic manipulations, and the narrative for Model 1 provides background information on the processes that create and maintain floodplain topography. The management output ‘riparian structure’ is a Model 1 output.

DRERIP Ecosystem Conceptual Model: Green sturgeon

California Department of Fish and Wildlife (CDFW) | December 27th, 2008

The purpose of this report is to develop a conceptual life history model of North American green sturgeon (Acipenser medirostris) and the factors that affect reproduction

The purpose of this report is to develop a conceptual life history model of North American green sturgeon (Acipenser medirostris) and the factors that affect reproduction, growth, and survival in the Sacramento and San Joaquin rivers and San Francisco Bay-Delta. This model can be used to organize, visualize, and evaluate how the complex life history of green sturgeon relates to the spatial and temporal variability of riverine and estuarine ecosystems and potential consequences of ecosystem restoration and water management alternatives. This model is compatible with the suite of environmental and species models developed by the Department of Fish and Game Ecosystem Restoration Program (ERP) to assess and prioritize proposed restoration actions for the Delta. The model has a geographic emphasis on the Sacramento River and Bay-Delta regions, though the entire distribution of green sturgeon must be considered when population level responses are of concern, due to the unique, highly-migratory life history of this species. The conceptual life history model incorporates information from numerous sources about green sturgeon, often relying upon life history information from populations outside the Southern Distinct Population Segment (DPS) and occasionally considering information from the sympatric white sturgeon (A. transmontanus). While surrogate information from other North American sturgeon could have been used in the model, the distinctive anadromous and ecological characteristics of green sturgeon limited the utility of these species’ information. Due to the limits of quantitative information about green sturgeon, this model is presented in a qualitative narrative with numerical information provided, when available. While it will not provide quantitative limits on species take relative to maintaining a stable population size, it could be further developed into a population forecasting model since it divides the life history into life history stages, transition probabilities, and factors whose affects on reproduction and survival could be quantified. Life history stage transitions are visualized in a series of life stage submodels highlighting the processes and relationships among ecological factors influencing the transition between stages (Figures 1 and 2). A complex set of conditions and processes are necessary to determine whether an individual fish completes the transition from one life stage to the next. Our knowledge of green sturgeon life history remains limited as to the relative importance of biotic and abiotic factors critical for maintaining self-sustaining populations of green sturgeon. Thus, the importance, predictability, and understanding of each of these linkages are identified in the model. Lastly, a similar characterization of independent stressors is undertaken to describe potential factors affecting survival during each life history stage in a known geographic region. This model is dynamic and not intended to be a final version. As new information becomes available, the model should be refined so managers and biologists have the most current information available.