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USGS2012

Automating calibration, sensitivity and uncertainty analysis of complex models using the R package Flexible Modeling Environment (FME): SWAT as an example

Parameter optimization and uncertainty issues are a great challenge for the application of large environmental models like the Soil and Water Assessment Tool (SWAT), which is a physically-based hydrological model for simulating water and nutrient cycles at the watershed scale. In this study, we present a comprehensive modeling environment for SWAT, including automated calibration, and sensitivity and uncertainty analysis capabilities through integration with the R package Flexible Modeling Environment (FME). To address challenges (e.g., calling the model in R and transferring variables between Fortran and R) in developing such a two-language coupling framework, 1) we converted the Fortran-based SWAT model to an R function (R-SWAT) using the RFortran platform, and alternatively 2) we compiled SWAT as a Dynamic Link Library (DLL). We then wrapped SWAT (via R-SWAT) with FME to perform complex applications including parameter identifiability, inverse modeling, and sensitivity and uncertainty analysis in the R environment. The final R-SWAT-FME framework has the following key functionalities: automatic initialization of R, running Fortran-based SWAT and R commands in parallel, transferring parameters and model output between SWAT and R, and inverse modeling with visualization. To examine this framework and demonstrate how it works, a case study simulating streamflow in the Cedar River Basin in Iowa in the United Sates was used, and we compared it with the built-in auto-calibration tool of SWAT in parameter optimization. Results indicate that both methods performed well and similarly in searching a set of optimal parameters. Nonetheless, the R-SWAT-FME is more attractive due to its instant visualization, and potential to take advantage of other R packages (e.g., inverse modeling and statistical graphics). The methods presented in the paper are readily adaptable to other model applications that require capability for automated calibration, and sensitivity and uncertainty analysis.

Environmental Modelling and Software↗

USGS2023

Modeling coho salmon (Oncorhynchus kisutch) population response to streamflow and water temperature extremes

Models that assess the vulnerability of freshwater species to shifting environmental conditions do not always account for short-duration extremes, which are increasingly common. Life cycle models for Pacific salmon ( Oncorhynchus spp.) generally focus on average conditions that fish experience during each life stage, yet many floods, low flows, and elevated water temperatures only last days to weeks. We developed a process-based life cycle model that links coho salmon ( Oncorhynchus kisutch ) abundance to daily streamflow and thermal regimes to assess: (1) “How does salmon abundance respond to short-duration floods, low flows, and high temperatures in glacier-, snow-, and rain-fed streams?” and (2) “How does the temporal resolution of flow and temperature data influence these responses?”. Our simulations indicate that short-duration extremes can reduce salmon abundance in some contexts. However, after daily flow and temperature data were aggregated into weekly and monthly averages, the impact of extreme events on populations declined. Our analysis demonstrates that novel modeling frameworks that capture daily variability in flow and temperature are needed to examine impacts of extreme events on Pacific salmon.

Article↗

USGS2018

Lions and leopards coexist without spatial, temporal or demographic effects of interspecific competition

1. Although interspecific competition plays a principle role in shaping species behaviour and demography, little is known about the population-level outcomes of competition between large carnivores, and the mechanisms that facilitate coexistence. 2. We conducted a multi-landscape analysis of two widely distributed, threatened large carnivore competitors to offer insight into coexistence strategies and assist with species-level conservation. 3. We evaluated how interference competition affects occupancy, temporal activity and population density of a dominant competitor, the lion (Panthera leo), and its subordinate competitor, the leopard (Panthera pardus). We collected camera-trap data over three years in ten study sites covering 5,070 km2. We used multispecies occupancy modelling to assess spatial responses in varying environmental and prey conditions and competitor presence, and examined temporal overlap and the relationship between lion and leopard densities across sites and years. 4. Results showed that both lion and leopard occupancy was independent of – rather than conditional on – their competitor’s presence across all environmental covariates. Marginal occupancy probability for leopard was higher in areas with more bushy, ‘hideable’ habitat, human (tourist) activity and topographic ruggedness, whereas lion occupancy decreased with increasing hideable habitat and increased with higher abundance of very large prey. Temporal overlap was high between carnivores and there was no significant relationship between species densities. 4. Lions pose a threat to the survival of individual leopards, but they exerted no tractable influence on leopard spatial or temporal dynamics. Furthermore, lions did not appear to suppress leopard populations, suggesting that intraguild competitors can coexist in the same areas without population decline. Aligned conservation strategies that promote functioning ecosystems, rather than target individual species, are therefore suggested to achieve cost- and space-effective conservation.

Journal of Animal Ecology↗

USGS2020

Managing for a changing climate: A bended interdisciplinary climate course

We developed a blended (or hybrid) interactive course— Managing for a Changing Climate —that provides a holistic view of climate change. The course results from communication with university students and natural and cultural resource managers as well as the need for educational efforts aimed at the public, legislators, and decision-makers. Content includes the components of the physical climate system, natural climate variability, anthropogenic drivers of climate change, climate models and projections, climate assessments, energy economics, environmental policy, vulnerabilities to climate hazards, impacts of climate change, and decision-making related to climate adaptation and mitigation efforts. To convey most of the content, the course-development team created over 50 short videos (3–10 min each) in partnership with experts from a variety of academic, government, and industry institutions. The blended course has been offered as an upper-division, undergraduate course in the Department of Geography and Environmental Sustainability and School of Meteorology (four times) and College of International Studies (in Italy, once) at the University of Oklahoma with over 100 total students. The course has also been presented online-only at no cost to the participants in four fall semesters with over 1,000 total registrations. Videos created for this course are freely available on the YouTube page of the South Central Climate Adaptation Science Center. This course and its associated materials comprise high-quality, formal climate training and education that can be adapted to other formal and informal education settings beyond the walls of the university.

Bulletin of the American Meteorological Society↗

USGS2020

Aquatic invasive species in the Chesapeake Bay drainage—Research-based needs and priorities of U.S. Geological Survey partners and collaborators

Executive Summary The U.S. Geological Survey (USGS) is revising the Chesapeake Bay-based science plan to align it with recent U.S. Department of Interior and USGS science priorities that include, as stated in the plan, providing “an integrated understanding of the factors affecting fish habitat, fish health, and landscape conditions” in Chesapeake Bay and its watershed. A report of partner agencies’ needs and priorities related to aquatic invasive species (AIS) science was identified as an informational gap; a report would help to further development of the science program related to aquatic animal health and habitat. This objective was addressed through review of pertinent documentation and conversations with representatives of State, Federal, and regional agencies with vested interests in AIS management in Chesapeake Bay and the Chesapeake Bay drainage area, and this document was produced to summarize the related findings. All agencies and organizations (13) reported that AIS are of general concern, with most stakeholder groups reporting AIS-related issues to be of high priority, including invasive fishes and invertebrates, invasive plants, and microbes including aquatic animal pathogens. Invasive fishes are of great concern to all partner agencies. Channa argus (northern snakehead) and Ictalurus furcatus (blue catfish) are high priority and represent the two most named AIS of concern for these agencies. Nine of 10 stakeholder groups listed northern snakehead as a high priority species, and 6 listed blue catfish as a high priority species as well. Pylodictis olivaris (flathead catfish), invasive crayfish species , and dressenid mussels were also prioritized by multiple partner groups, each receiving specific mention by at least 3 of the 10 stakeholder groups in discussions or documents. Invasive carp, such as Hypophthalmichthys molatrix (silver carp), also received mention by multiple agencies (3 of the 10 stakeholder groups) because these fish represent priority AIS in nearby watersheds and a threat for introduction and dissemination within the Chesapeake Bay watershed from these neighboring regions. Invasive plants are among priority species, and Hydrilla verticillata (hydrilla) topped the list. Hydrilla was reported as a priority species by 5 of the stakeholder groups queried. Trapa natans and T. bispinosa (water chestnut), Phragmites australis (common reed), and Lythrum salicaria (purple loosestrife) were also among the aquatic invasive plants that were prioritized by multiple partner agencies. Multiple stakeholder groups (5 of the 10 groups) also considered Didymosphenia geminata (didymo) and various aquatic animal pathogens among their priority AIS for management considerations. Science needs that were recurrently indicated by stakeholders to support management of invasive species include Technology to enhance biosurveillance capability, such as reliable environmental DNA based detection methodology; Risk assessment modeling to forewarn of and prioritize AIS-related threats; Increased information and intervention methods related to vectors and pathways of AIS introductions; Increased information about the biology and life history of AIS, including information related to trophic interactions, health and disease, and distribution and abundance; and Potential applications of mitigation strategies, including genetically based biocontrol mechanisms. Potential next steps to address the science needs include Development of biosurveillance and risk assessment tools for identification of AIS in proactive management; Development of proactive management techniques to prevent AIS introductions through recognized vectors and pathways; Development of interagency biosurveillance programs to best utilize personnel, funds, and other resources among interested agencies and organizations; Investigations to address life history, consequences, and movement/dissemination of top priority invasive species in the region; Investigations to determine the potential for novel mitigation technologies, such as the application of synthetic biological (genetic) control methods; and Investigations with focus on emerging and high priority AIS in the region, including fishes (blue catfish, flathead catfish, northern snakehead), invertebrates (invasive crayfish and mollusks) and plants (hydrilla, water chestnut, phragmites).

Virginia, Maryland, Delaware, West Virginia, Penns↗

USGS2021

Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach

System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socio-environmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socio-environmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems.

Environmental Modelling and Software↗

USGS2022

Parameterizing an aeolian erosion model for rangelands

Aeolian processes are fundamental to arid and semi-arid ecosystems, but modeling approaches are poorly developed for assessing impacts of management and environmental change on sediment transport rates over meaningful spatial and temporal scales. For model estimates to provide value, estimates of sediment flux that encapsulate intra- and inter-annual and spatial variability are needed. Further, it is important to quantify and communicate transparent estimates of model uncertainty to users. Here, we present a wind erosion and dust emission model parameterized for rangelands using a Generalized Likelihood Uncertainty Estimation framework. Modeled horizontal sediment flux was calibrated using data from five diverse grassland and shrubland sites from the USDA National Wind Erosion Research Network. Observations of wind speed, vegetation height, length of gaps between vegetation, and percent bare ground were used as model inputs. Horizontal sediment flux estimates from 10,000 independently selected parameter sets were compared to flux observations from 44 ∼ month-long collection periods to calculate a likelihood measure for each model. Results show good agreement for individual sampling periods across sites with few observations falling outside prediction bounds and a one-to-one relationship between median predictions and observations. Additionally, combined distributions of sediment flux estimates from all sample periods for a given site closely approximated the probability of observing a given flux at that site. These results suggest AERO effectively represents temporal variability in aeolian transport rates at rangeland sites and provides robust assessments suitable for assessing land health and better predicting changes in air quality and the impacts of land management activities.

Aeolian Research↗

USGS1984

Ground-water models as a management tool in Florida

Highly sophisticated computer models provide powerful tools for analyzing historic data and for simulating future water levels, water movement, and water chemistry under stressed conditions throughout the ground-water system in Florida. Models that simulate the movement of heat and subsidence of land in response to aquifer pumping also have potential for application to hydrologic problems in the State. Florida, with 20 ground-water modeling studies reported since 1972, has applied computer modeling techniques to a variety of water-resources problems. Models in Florida generally have been used to provide insight to problems of water supply, contamination, and impact on the environment. The model applications range from site-specific studies, such as estimating contamination by wastewater injection at St. Petersburg, to a regional model of the entire State that may be used to assess broad-scale environmental impact of water-resources development. Recently, groundwater models have been used as management tools by the State regulatory authority to permit or deny development of water resources. As modeling precision, knowledge, and confidence increase, the use of ground-water models will shift more and more toward regulation of development and enforcement of environmental laws. (USGS)

Water-Resources Investigations Report↗

USGS2000

Testing a multi-tiered stress-gradient model for risk assessment using sediment constituents from coral reef environments

Coral reefs are threatened worldwide by stresses ranging from local to global in extent. One of the major challenges in studies of reef decline is understanding how to distinguish between changes resulting from natural, anthropogenic, local, and global environmental perturbations. As such, a conceptual risk-assessment model is developed that includes tiers for natural stresses, global/regional stresses, and local anthropogenic stresses.

Conference Paper↗

USGS2024

Fish size structures in lakes of the Lower Mississippi River floodplain

The Lower Mississippi River has a floodplain that includes >1350 perennial lakes carved by shifts in river courses and other hydro-fluvial processes over eons. Notwithstanding their similar provenances, these waterbodies exhibit an immense variety of morphologies and successional stages that illustrate their natural trajectory from aquatic to forested wetlands. A result of this geographical, morphological and temporal diversity is dynamic and varied fish communities. We examined how size structures of fish communities in these floodplain lakes were associated with key in-lake and off-lake environmental drivers. Fish lengths were collected with standardised procedures in a sample of 30 of these lakes to construct a lake-by-length group matrix. Likewise, in-lake and off-lake environmental descriptors were collected to construct a lake-by-covariate matrix. Distance-based linear models were used to assess associations between fish size structure and environmental descriptors. Smaller fish were typically associated with increasing levels of turbidity, chlorophyll- a , phycocyanin and surrounding agriculture. Shallow, hypereutrophic floodplain lakes associated with agricultural landscapes and reduced connectivity experience harsh physicochemical environments. These conditions appeared to hinder the formation of sustained fish communities but may confer a survival advantage to juveniles or small short-lived species. Conversely, larger fish were associated with increasing lake depth, water clarity, connectivity, and extent of surrounding forests-wetlands. Enhanced stability and size structure were observed in communities residing in deeper and clearer lakes, suggesting that these conditions facilitated the development of longer-lived species spanning multiple age groups. The enhanced connectivity that facilitated this increased stability also permitted the presence of larger itinerant species. Size-structure assessments can serve as a valuable ecological and biodiversity indicator in floodplain lakes. Size-structure assessments could supplement and, depending on objectives, even supplant conventional taxonomic analyses, and enhance surveillance of this vast and important natural resource.

Arkansas, Louisiana, Mississippi, Missouri, Tennes↗

USGS2011

Assessing conceptual models for subsurface reactive transport of inorganic contaminants

In many subsurface situations where human health and environmental quality are at risk (e.g., contaminant hydrogeology petroleum extraction, carbon sequestration, etc.),scientists and engineers are being asked by federal agency decision-makers to predict the fate of chemical species under conditions where both reactions and transport are processes of first-order importance. In 2002, a working group (WG) was formed by representatives of the U.S. Geological Survey, Environmental Protection Agency, Department of Energy Nuclear Regulatory Commission, Department of Agriculture, and Army Engineer Research and Development Center to assess the role of reactive transport modeling (RTM) in addressing these situations. Specifically the goals of the WG are to (1) evaluate the state of the art in conceptual model development and parameterization for RTM, as applied to soil,vadose zone, and groundwater systems, and (2) prioritize research directions that would enhance the practical utility of RTM.

Eos, Transactions, American Geophysical Union↗

USGS2007

Developing methods to assess and predict the population and community level effects of environmental contaminants

The field of ecological toxicity seems largely to have drifted away from what its title implies—assessing and predicting the ecological consequences of environmental contaminants—moving instead toward an emphasis on individual effects and physiologic case studies. This paper elucidates how a relatively new ecological methodology, interaction assessment (INTASS), could be useful in addressing the field's initial goals. Specifically, INTASS is a model platform and methodology, applicable across a broad array of taxa and habitat types, that can be used to construct population dynamics models from field data. Information on environmental contaminants and multiple stressors can be incorporated into these models in a form that bypasses the problems inherent in assessing uptake, chemical interactions in the environment, and synergistic effects in the organism. INTASS can, therefore, be used to evaluate the effects of contaminants and other stressors at the population level and to predict how changes in stressor levels or composition of contaminant mixtures, as well as various mitigation measures, might affect population dynamics.

Integrated Environmental Assessment and Management↗

USGS2010

A deposit model for Mississippi Valley-Type lead-zinc ores

This report is a descriptive model of Mississippi Valley-Type (MVT) lead-zinc deposits that presents their geological, mineralogical and geochemical attributes and is part of an effort by the U.S. Geological Survey Mineral Resources Program to update existing models and develop new models that will be used for an upcoming national mineral resource assessment. This deposit modeling effort by the USGS is intended to supplement previously published models for use in mineral-resource and mineral-environmental assessments. Included in this report are geological, geophysical and geochemical assessment guides to assist in mineral resource estimation. The deposit attributes, including grade and tonnage of the deposits described in this report are based on a new mineral deposits data set of all known MVT deposits in the world. Mississippi Valley-Type (MVT) lead-zinc deposits are found throughout the world but the largest, and more intensely researched deposits occur in North America. The ores consist mainly of sphalerite, galena, and generally lesser amounts of iron sulfides. Silver is commonly an important commodity, whereas Cu is generally low, but is economically important in some deposits. Gangue minerals may include carbonates (dolomite, siderite, ankerite, calcite), and typically minor barite. Silicification of the host rocks (or quartz gangue) is generally minor, but may be abundant in a few deposits. The deposits have a broad range of relationships with their host rocks that includes stratabound, and discordant ores; in some deposits, stratiform and vein ore are important. The most important characteristics of MVT ore deposits are that they are hosted mainly by dolostone and limestone in platform carbonate sequences and usually located at flanks of basins, orogenic forelands, or foreland thrust belts inboard of the clastic rock-dominated passive margin sequences. They have no spatial or temporal relation to igneous rocks, which distinguishes them from skarn or other intrusive rock-related Pb-Zn ores. Abundant evidence has shown that the ore fluids were derived mainly from evaporated seawater and were driven within platform carbonates by large-scale tectonic events. MVT deposits formed mainly during the Phanerozoic with more than 80 percent of the deposits hosted in Phanerozoic rocks and less than 20 percent in Precambrian rocks. Phanerozoic-hosted MVT deposits also account for 94 percent of total MVT ore, and 93 percent of total MVT lead and zinc metal. Many MVT deposits formed during Devonian to Permian time, corresponding to a series of intense tectonic events during assimilation of Pangea. The second most important period for MVT deposit genesis was Cretaceous to Tertiary time when microplate assimilation affected the western margin of North America and Africa-Eurasia. Many subtypes or alternative classifications have been applied to MVT deposits. These alternative classifications reflect geographic and or specific geological features that some workers believe set them apart as unique (for example, Appalachian-, Alpine-, Reocin-, Irish-, Viburnum trend-types). However, we do not consider these alternative classifications or sub-types to be sufficiently different to warrant using them. This report also describes the geoenvironmental characteristic of MVT deposits. The response of MVT ores in the supergene environment is buffered by their placement in carbonate host rocks which commonly results in near-neutral associated drainage water. The geoenvironmental features and anthropogenic mining effects presented in this report illustrates this important environmental aspect of MVT deposits which separates them from other deposit types (especially coal, VHMS, Cu-porphyry, SEDEX, acid-sulfate polymetallic vein).

Scientific Investigations Report↗

USGS2014

Combining demographic and genetic factors to assess population vulnerability in stream species

Accelerating climate change and other cumulative stressors create an urgent need to understand the influence of environmental variation and landscape features on the connectivity and vulnerability of freshwater species. Here, we introduce a novel modeling framework for aquatic systems that integrates spatially explicit, individual‐based, demographic and genetic (demogenetic) assessments with environmental variables. To show its potential utility, we simulated a hypothetical network of 19 migratory riverine populations (e.g., salmonids) using a riverscape connectivity and demogenetic model (CDFISH). We assessed how stream resistance to movement (a function of water temperature, fluvial distance, and physical barriers) might influence demogenetic connectivity, and hence, population vulnerability. We present demographic metrics (abundance, immigration, and change in abundance) and genetic metrics (diversity, differentiation, and change in differentiation), and combine them into a single vulnerability index for identifying populations at risk of extirpation. We considered four realistic scenarios that illustrate the relative sensitivity of these metrics for early detection of reduced connectivity: (1) maximum resistance due to high water temperatures throughout the network, (2) minimum resistance due to low water temperatures throughout the network, (3) increased resistance at a tributary junction caused by a partial barrier, and (4) complete isolation of a tributary, leaving resident individuals only. We then applied this demogenetic framework using empirical data for a bull trout ( Salvelinus confluentus ) metapopulation in the upper Flathead River system, Canada and USA, to assess how current and predicted future stream warming may influence population vulnerability. Results suggest that warmer water temperatures and associated barriers to movement (e.g., low flows, dewatering) are predicted to fragment suitable habitat for migratory salmonids, resulting in the loss of genetic diversity and reduced numbers in certain vulnerable populations. This demogenetic simulation framework, which is illustrated in a web‐based interactive mapping prototype, should be useful for evaluating population vulnerability in a wide variety of dendritic and fragmented riverscapes, helping to guide conservation and management efforts for freshwater species.

Montana↗

USGS2012

Wildlife contact analysis: Emerging methods, questions, and challenges

Recent technological advances, such as proximity loggers, allow researchers to collect complete interaction histories, day and night, among sampled individuals over several months to years. Social network analyses are an obvious approach to analyzing interaction data because of their flexibility for fitting many different social structures as well as the ability to assess both direct contacts and indirect associations via intermediaries. For many network properties, however, it is not clear whether estimates based upon a sample of the network are reflective of the entire network. In wildlife applications, networks may be poorly sampled and boundary effects will be common. We present an alternative approach that utilizes a hierarchical modeling framework to assess the individual, dyadic, and environmental factors contributing to variation in the interaction rates and allows us to estimate the underlying process variation in each. In a disease control context, this approach will allow managers to focus efforts on those types of individuals and environments that contribute the most toward super-spreading events. We account for the sampling distribution of proximity loggers and the non-independence of contacts among groups by only using contact data within a group during days when the group membership of proximity loggers was known. This allows us to separate the two mechanisms responsible for a pair not contacting one another: they were not in the same group or they were in the same group but did not come within the specified contact distance. We illustrate our approach with an example dataset of female elk from northwestern Wyoming and conclude with a number of important future research directions.

Behavioral Ecology and Sociobiology↗

USGS2016

Integrating geological archives and climate models for the mid-Pliocene warm period

The mid-Pliocene Warm Period (mPWP) offers an opportunity to understand a warmer-than-present world and assess the predictive ability of numerical climate models. Environmental reconstruction and climate modelling are crucial for understanding the mPWP, and the synergy of these two, often disparate, fields has proven essential in confirming features of the past and in turn building confidence in projections of the future. The continual development of methodologies to better facilitate environmental synthesis and data/model comparison is essential, with recent work demonstrating that time-specific (time-slice) syntheses represent the next logical step in exploring climate change during the mPWP and realizing its potential as a test bed for understanding future climate change.

Nature Communications↗

USGS2010

Propagule pressure and stream characteristics influence introgression: Cutthroat and rainbow trout in British Columbia

Hybridization and introgression between introduced and native salmonids threaten the continued persistence of many inland cutthroat trout species. Environmental models have been developed to predict the spread of introgression, but few studies have assessed the role of propagule pressure. We used an extensive set of fish stocking records and geographic information system (GIS) data to produce a spatially explicit index of potential propagule pressure exerted by introduced rainbow trout in the Upper Kootenay River, British Columbia, Canada. We then used logistic regression and the information-theoretic approach to test the ability of a set of environmental and spatial variables to predict the level of introgression between native westslope cutthroat trout and introduced rainbow trout. Introgression was assessed using between four and seven co-dominant, diagnostic nuclear markers at 45 sites in 31 different streams. The best model for predicting introgression included our GIS propagule pressure index and an environmental variable that accounted for the biogeoclimatic zone of the site (r 2 = 0.62). This model was 1.4 times more likely to explain introgression than the next-best model, which consisted of only the propagule pressure index variable. We created a composite model based on the model-averaged results of the seven top models that included environmental, spatial, and propagule pressure variables. The propagule pressure index had the highest importance weight (0.995) of all variables tested and was negatively related to sites with no introgression. This study used an index of propagule pressure and demonstrated that propagule pressure had the greatest influence on the level of introgression between a native and introduced trout in a human-induced hybrid zone. ?? 2010 by the Ecological Society of America.

Ecological Applications↗

USGS2022

Comparisons of Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) sea-ice projections in polar bear (Ursus maritimus) ecoregions during the 21st century

Climate model projections are commonly used to assess potential impacts of global warming on a breadth of social, economic, and environmental topics. Modeling centers throughout the world coordinate to apply a consistent suite of radiative forcing experiments so that all model outputs can be collectively analyzed and compared. Three generations of model outputs have been produced and made available to the scientific community through the Coupled Model Intercomparison Project (CMIP): CMIP3 disseminated during the mid-2000s, CMIP5 during the early-2010s, and CMIP6 during the late-2010s. Twenty-first century sea-ice projections from CMIP3 and CMIP5 models have been used in Bayesian network assessments of how climate change could impact the future persistence of polar bears ( Ursus maritimus ) throughout their range. In this report, we compare sea-ice projections by CMIP6 models to those of CMIP5 models in each of four polar bear ecoregions over the 21st century. We evaluate differences between the two CMIP generations with respect to other sources of variability that affect uncertainties of the model projections: (1) variability from different models; (2) variability from different greenhouse gas emissions scenarios; and (3) natural (internal) variability in the earth’s climate system. We found that natural variability as well as that attributable to models dominated uncertainties in sea-ice projections in all months and ecoregions during the first half of the 21st century, while emissions scenarios dominated uncertainties during the late 21st century. By comparison, we found only slight differences between the CMIP6 and CMIP5 model projections of sea ice. Applying CMIP6 instead of CMIP5 sea-ice projections to the polar bear Bayesian network model developed in 2016, therefore, would not qualitatively change the population status outcomes published therein.

Open-File Report↗