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USGS2021

Paths to computational fluency for natural resource educators, researchers, and managers

Natural resource management and supporting research teams need computational fluency in the data and model-rich 21st century. Computational fluency describes the ability of practitioners and scientists to conduct research and represent natural systems within the computer's environment. Advancement in information synthesis for natural resource management requires more sophisticated computational approaches, as well as reproducible, reusable, extensible, and transferable methods. Despite this importance, many new and current natural resource practitioners lack computational fluency and no common set of recommended resources and practices exist for learning these skills. Broadly, attaining computational fluency entails moving beyond the simple use of computers to applying sound computational principles and methods and including computational experts (such as computer scientists) on research teams. Our path for computational fluency includes using open-source tools when possible; reproducible data management, statistics, and modeling; understanding and applying the benefits of basic computer programming to carry out more complex procedures; tracking code with version control; working in controlled computer environments; and using advanced computing resources.

Natural Resource Modelling↗

USGS2013

National assessment of geologic carbon dioxide storage resources: Summary

The U.S. Geological Survey (USGS) recently completed an evaluation of the technically accessible storage resource ( TA SR ) for carbon dioxide (CO 2 ) for 36 sedimentary basins in the onshore areas and State waters of the United States. The TA SR is an estimate of the geologic storage resource that may be available for CO 2 injection and storage and is based on current geologic and hydrologic knowledge of the subsurface and current engineering practices. By using a geology-based probabilistic assessment methodology, the USGS assessment team members obtained a mean estimate of approximately 3,000 metric gigatons (Gt) of subsurface CO 2 storage capacity that is technically accessible below onshore areas and State waters; this amount is more than 500 times the 2011 annual U.S. energy-related CO 2 emissions of 5.5 Gt (U.S. Energy Information Administration, 2012, http://www.eia.gov/environment/emissions/carbon/). In 2007, the Energy Independence and Security Act (Public Law 110–140) directed the U.S. Geological Survey to conduct a national assessment of geologic storage resources for CO 2 in consultation with the U.S. Environmental Protection Agency, the U.S. Department of Energy, and State geological surveys. The USGS developed a methodology to estimate storage resource potential in geologic formations in the United States (Burruss and others, 2009, USGS Open-File Report (OFR) 2009–1035; Brennan and others, 2010, USGS OFR 2010–1127; Blondes, Brennan, and others, 2013, USGS OFR 2013–1055). In 2012, the USGS completed the assessment, and the results are summarized in this Fact Sheet and are provided in more detail in companion reports (U.S. Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team, 2013a,b; see related reports at right). The goal of this project was to conduct an initial assessment of storage capacity on a regional basis, and results are not intended for use in the evaluation of specific sites for potential CO 2 storage. The national assessment was a geology-based examination of all sedimentary basins in the onshore and State waters area of the United States that contain storage assessment units (SAUs) that could be defined according to geologic and hydrologic characteristics. Although geologic storage of CO 2 may be possible in some areas not assessed by the USGS, the SAUs identified in this assessment represent those areas within sedimentary basins that met the assessment criteria. A geologic description of each SAU was prepared; descriptions for SAUs in several basins are in Warwick and Corum (2012, USGS OFR 2012–1024).

Fact Sheet↗

USGS1986

Reconnaissance of the water resources and potential effects of mining of the Joliet-Fromberg coal tract, Carbon County, Montana

The Joliet-Fromberg coal tract in Carbon County, Montana, contains subbituminous to bituminous coal suitable for underground mining. A reconnaissance study of the area was conducted to identify water resources of the coal tract and to determine general effects that underground mining could have on the water resources. Surface-water resources consist of Elbow Creek, a small perennial stream that drains most of the area, plus irrigation water diverted into the basin from Rock Creek and the Clarks Fork Yellowstone River. Groundwater resources consist of sandstone aquifers in several formations of Late Cretaceous age and alluvial aquifers of Pleistocene and Holocene age. Chemical analyses were made of water in Elbow Creek and water from seven wells in the area. Water from Elbow Creek is suitable for use by all livestock, based on the concentration of dissolved solids. Water from most sampled wells had dissolved-solids concentrations larger than the maximum (500 milligrams/L) recommended by the U.S. Environmental Protection Agency for public water supply. Effects of underground mining on water resources would be minimal. The Bridger coal bed in the Upper Cretaceous Eagle Sandstone has no significant hydraulic connection with Elbow Creek in most of the area and the Bridger coal bed does not appear to be a significant aquifer. Mining and dewatering of the coal could temporarily lower water levels in aquifers overlying the coal if mining causes subsidence and fracturing of rocks above the mine workings. (USGS)

Montana↗

USGS2022

Advancing geophysical techniques to image a stratigraphic hydrothermal resource

Sedimentary-hosted geothermal energy systems are permeable structural, structural-stratigraphic, and/or stratigraphic horizons with sufficient temperature for direct use and/or electricity generation. Sedimentary-hosted (i.e., stratigraphic) geothermal reservoirs may be present in multiple locations across the central and eastern Great Basin of the USA, thereby constituting a potentially large base of untapped, economically accessible energy resources. Sandia National Laboratories has partnered with a multi-disciplinary group of collaborators to evaluate a stratigraphic system in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The goal of this study is to inform an optimized strategy for subsequent exploration and development of this and analogous resources. Building from prior Nevada Play Fairway Analysis (PFA), this team is primarily 1) collecting additional geophysical data, 2) employing novel joint geophysical inversion/modeling techniques to update existing 3D geologic models, and 3) integrating the geophysical results to produce a working, geologically constrained thermo-hydrological reservoir model. Prior PFA work highlights Steptoe Valley as a favorable resource basin that likely has both sedimentary and hydrothermal characteristics. However, there remains significant uncertainty on the nature and architecture of the resource(s) at depth, which increases the risk in exploratory drilling. Newly acquired gravity, magnetic, magnetotelluric, and controlled-source electromagnetic data, in conjunction with new and preceding geoscientific measurements and observations, are being integrated and evaluated in this study for efficacy in understanding stratigraphic geothermal resources and mitigating exploration risk. Furthermore, the influence of hydrothermal activity on sedimentary-hosted reservoirs in favorable structural settings (i.e., whether fault-controlled systems may locally enhance temperature and permeability in some deep stratigraphic reservoirs) will also be evaluated. This paper provides details and current updates on the course of this study in-progress.

Geothermal Resources Council Transactions↗

USGS2016

Katmai National Park and Preserve and Alagnak Wild River: Geologic resources inventory report

The Geologic Resources Inventory (GRI) is one of 12 inventories funded by the National Park Service (NPS) Inventory and Monitoring Program. The Geologic Resources Division of the NPS Natural Resource Stewardship and Science Directorate administers the GRI. This GRI report was written for resource managers to support science-informed decision making. It may also be useful for interpretation. The report was prepared using available geologic information. Chapters of the report discuss distinctive geologic features and processes, describe the geologic history leading to the present- day landscape, highlight geologic issues facing resource managers, and provide information about the associated GRI geologic map data. A poster (Plate 1, in pocket) illustrates these data.

Alaska↗

USGS2020

Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty

Populations of invasive species often spread heterogeneously across a landscape, consisting of local populations that cluster in space but are connected by dispersal. A fundamental dilemma for invasive species control is how to optimally allocate limited fiscal resources across local populations. Theoretical work based on perfect knowledge of demographic connectivity suggests that targeting local populations from which migrants originate (sources) can be optimal. However, demographic processes such as abundance and dispersal can be highly uncertain, and the relationship between local population density and damage costs (damage function) is rarely known. We used a metapopulation model to understand how budget and uncertainty in abundance, connectivity, and the damage function, together impact return on investment (ROI) for optimal control strategies. Budget, observational uncertainty, and the damage function had strong effects on the optimal resource allocation strategy. Uncertainty in dispersal probability was the least important determinant of ROI. The damage function determined which resource prioritization strategy was optimal when connectivity was symmetric but not when it was asymmetric. When connectivity was asymmetric, prioritizing source populations had a higher ROI than allocating effort equally across local populations, regardless of the damage function, but uncertainty in connectivity structure and abundance reduced ROI of the optimal prioritization strategy by 57% on average depending on the control budget. With low budgets (monthly removal rate of 6.7% of population), there was little advantage to prioritizing resources, especially when connectivity was high or symmetric, and observational uncertainty had only minor effects on ROI. Allotting funding for improved monitoring appeared to be most important when budgets were moderate (monthly removal of 13–20% of the population). Our result showed that multiple sources of observational uncertainty should be considered concurrently for optimizing ROI. Accurate estimates of connectivity direction and abundance were more important than accurate estimates of dispersal rates. Developing cost-effective surveillance methods to reduce observational uncertainties, and quantitative frameworks for determining how resources should be spatially apportioned to multiple monitoring and control activities are important and challenging future directions for optimizing ROI for invasive species control programs.

Ecological Applications↗

USGS2024

Seasonal resource selection of a grassland bird in a dynamic landscape: Importance of a heterogeneous landscape

Habitat loss and fragmentation are a growing threat to wildlife, and a better understanding of these landscape processes is needed to mitigate their effects on species populations. Grassland biomes are among the most imperiled ecosystems in the world, and grassland birds are experiencing significant population declines in North America. Understanding how species respond to differences in resource availabilities across spatiotemporal extents is critical to determining animals' distributions. Here, we investigated the relationship of landscape attributes to spatiotemporal distribution of a grassland bird, the ring-necked pheasant ( Phasianus colchicus ), which has experienced population declines in the Midwest, USA. Pheasant declines have been attributed to two anthropogenic stressors, land use change and climate change. In this study, we evaluated the effect of landscape attributes (composition and configuration) on the home-range size and resource selection of pheasants. We used a 95% fixed kernel estimator to estimate home-range size and identified scales at which landscape features influenced home-range sizes. We quantified landscape features within radii of 250, 500, and 1000 m (i.e., local to broader spatial scales) from the home-range center. We also used resource selection functions to predict the home-range placement (second order) and resource selection within home ranges (third order) of pheasants during winter, pre-nesting, and nesting seasons. We developed multi-scale predictions of pheasant resource selection and identified wetlands, grasslands, Conservation Reserve Program (CRP) grasslands, and small grains as land cover types used by pheasants to fulfill their life requirements. Our results indicated home ranges were more likely to be in a landscape with more CRP, wetlands, and grasslands; more connected grasslands; and a greater number of grassland patches. Pheasants also selected heterogeneous landscape and avoided row crops at both orders of selection. Maintaining habitat heterogeneity, by managing landscapes composed of a high proportion of grasslands and CRP surrounded by small grains and wetlands, could enhance the benefits of local management practices for pheasants. Collectively, insights obtained from our study can advance habitat conservation efforts for similar grassland birds and consequently are of broad utility to biologists and wildlife managers.

South Dakota↗

USGS2022

Dynamic sensitivity to resource availability influences population responses to mismatches in a shorebird

Climate change has caused shifts in seasonally recurring biological events leading to the temporal decoupling of consumer-resource pairs – i.e., phenological mismatching. Although mismatches often affect individual fitness, they do not invariably scale up to affect populations, making it difficult to assess the risk they pose. Individual variation may contribute to this inconsistency, with changes in resource availability and consumer needs leading mismatches to have different outcomes over time. Nevertheless, most models estimate a consumer’s match from a single timepoint, potentially obscuring when mismatches matter to populations. We analyzed how the effects of mismatches varied over time by studying precocial Hudsonian godwit ( Limosa haemastica) chicks and their invertebrate prey from 2009 to 2019. We developed individual and population level models to determine how age-specific variation affect the relationship between godwits and resource availability. We found that periods with abundant resources led to higher growth and survival of godwit chicks, but also that chick survival was increasingly related to the availability of larger prey as chicks aged. At the population level, estimates of mismatches using age-structured consumer demand explained more variation in annual godwit fledging rates than more commonly used alternatives. Our study suggests that modeling the effects of mismatches as the disrupted interaction between dynamic consumer needs and resource availability clarifies when mismatches matter to both individuals and populations.

Alaska↗

USGS2023

Application of the technology readiness levels framework to natural resource management tools

Technology advancements in fisheries science can provide useful tools to support natural resource management and conservation. However, new technologies may also present challenges for decision makers due to the lack of a standardized process to assess technologies for consideration within management plans. Future technology development in fishery and water resources could benefit from a framework that assigns an appropriate technology development stage and defines the readiness for implementation. Technology Readiness Levels (TRL) are one established research and development scale used throughout engineering and related disciplines that could be applied to natural resource management tools. The TRL assess the maturity of a technology from nascent idea through a fully developed technology. Steps within this scale could provide a general framework for researchers to follow when planning and conducting studies, while similarly providing a standard scale for resource managers to assess readiness for technology transfer and implementation. The goal of this paper is to describe TRL in the context of natural resource management tools and offer this existing framework as one option to facilitate communication between researchers and managers.

Fisheries↗

USGS2023

A novel approach to assessing natural resource injury with Bayesian networks

Quantifying the effects of environmental stressors on natural resources is problematic because of complex interactions among environmental factors that influence endpoints of interest. This complexity, coupled with data limitations, propagates uncertainty that can make it difficult to causally associate specific environmental stressors with injury endpoints. The Natural Resource Damage Assessment and Restoration (NRDAR) regulations under the Comprehensive Environmental Response, Compensation, and Liability Act and Oil Pollution Act aim to restore natural resources injured by oil spills and hazardous substances released into the environment; exploration of alternative statistical methods to evaluate effects could help address NRDAR legal claims. Bayesian networks (BNs) are statistical tools that can be used to estimate the influence and interrelatedness of abiotic and biotic environmental variables on environmental endpoints of interest. We investigated the application of a BN for injury assessment using a hypothetical case study by simulating data of acid mine drainage (AMD) affecting a fictional stream-dwelling bird species. We compared the BN-generated probability estimates for injury with a more traditional approach using toxicity thresholds for water and sediment chemistry. Bayesian networks offered several distinct advantages over traditional approaches, including formalizing the use of expert knowledge, probabilistic estimates of injury using intermediate direct and indirect effects, and the incorporation of a more nuanced and ecologically relevant representation of effects. Given the potential that BNs have for natural resource injury assessment, more research and field-based application are needed to determine their efficacy in NRDAR. We expect the resulting methods will be of interest to many US federal, state, and tribal programs devoted to the evaluation, mitigation, remediation, and/or restoration of natural resources injured by releases or spills of contaminants

Integrated Environmental Assessment and Management↗

USGS2015

Habitat manipulation influences northern bobwhite resource selection on a reclaimed surface mine

More than 600,000 ha of mine land have been reclaimed in the eastern United States, providing large contiguous tracts of early successional vegetation that can be managed for northern bobwhite ( Colinus virginianus ). However, habitat quality on reclaimed mine land can be limited by extensive coverage of non-native invasive species, which are commonly planted during reclamation. We used discrete-choice analysis to investigate bobwhite resource selection throughout the year on Peabody Wildlife Management Area, a 3,330-ha reclaimed surface mine in western Kentucky. We used a treatment-control design to study resource selection at 2 spatial scales to identify important aspects of mine land vegetation and whether resource selection differed between areas with habitat management (i.e., burning, disking, herbicide; treatment) and unmanaged units (control). Our objectives were to estimate bobwhite resource selection on reclaimed mine land and to estimate the influence of habitat management practices on resource selection. We used locations from 283 individuals during the breeding season (1 Apr–30 Sep) and 136 coveys during the non-breeding season (1 Oct–Mar 31) from August 2009 to March 2014. Individuals were located closer to shrub cover than would be expected at random throughout the year. During the breeding season, individuals on treatment units used areas with smaller contagion index values (i.e., greater interspersion) compared with individuals on control units. During the non-breeding season, birds selected areas with greater shrub-open edge density compared with random. At the microhabitat scale, individuals selected areas with increased visual obstruction >1 m aboveground. During the breeding season, birds were closer to disked areas (linear and non-linear) than would be expected at random. Individuals selected non-linear disked areas during winter but did not select linear disked areas (firebreaks) because they were planted to winter wheat each fall and lacked cover during the non-breeding season. Individuals also selected areas treated with herbicide to control sericea lespedeza ( Lespedeza cuneata ) throughout the year. During the breeding season, bobwhites avoided areas burned during the previous dormant season. Habitat quality of reclaimed mine lands may be limited by a lack of shrub cover and extensive coverage of non-native herbaceous vegetation. Managers aiming to increase bobwhite abundance should focus on increasing interspersion of shrub cover, with no area >100 m from shrub cover. We suggest disking and herbicide application to control invasive species and improve the structure and composition of vegetation for bobwhites.

Kentucky↗

USGS2008

The arctic water resource vulnerability index: An integrated assessment tool for community resilience and vulnerability with respect to freshwater

People in the Arctic face uncertainty in their daily lives as they contend with environmental changes at a range of scales from local to global. Freshwater is a critical resource to people, and although water resource indicators have been developed that operate from regional to global scales and for midlatitude to equatorial environments, no appropriate index exists for assessing the vulnerability of Arctic communities to changing water resources at the local scale. The Arctic Water Resource Vulnerability Index (AWRVI) is proposed as a tool that Arctic communities can use to assess their relative vulnerability-resilience to changes in their water resources from a variety of biophysical and socioeconomic processes. The AWRVI is based on a social-ecological systems perspective that includes physical and social indicators of change and is demonstrated in three case study communities/watersheds in Alaska. These results highlight the value of communities engaging in the process of using the AWRVI and the diagnostic capability of examining the suite of constituent physical and social scores rather than the total AWRVI score alone. ?? 2008 Springer Science+Business Media, LLC.

Environmental Management↗

USGS2005

Available nitrogen: A time-based study of manipulated resource islands

Spatial and temporal heterogeneity of available nitrogen are critical determinants of the distribution and abundance of plants and animals in ecosystems. Evidence for the resource island theory suggests that soils below tree and shrub canopies contain higher amounts of resources, including available nitrogen, than are present in interspace areas. Disturbances, such as prescribed fire and tree removal, are common management practices in shrub-woodland ecosystems, but it is not known if these practices affect resource islands. We examined temporal variation in resource islands of available nitrogen and their retention after fire and woody plant removal. From August 1997 to October 1998, soil nitrate (NO 3 − ) and ammonium (NH 4 + ) were measured monthly from canopy and interspace plots within four juniper-sagebrush sites along a precipitation gradient in central Oregon, USA. At each site, soil samples were collected from untreated plots, plots in which woody plants were removed, and those treated with prescribed fire in fall 1997. In burned treatments, canopy concentrations were significantly higher than interspace concentrations throughout the measurement period. Canopy NO 3 − and NH 4 + concentrations were significantly higher on burned vs . unburned treatments for four months after fire. After woody plant removal, NO 3 − and NH 4 + concentrations did not differ from the controls. Untreated control areas had higher NO 3 − and NH 4 + concentrations under juniper canopies for nearly all months. Wetter sites had smaller differences between canopy and interspace concentrations through time than did the two drier sites. In relation to NO 3 − and NH 4 + in this ecosystem, resource islands appear to be more ephemeral in wetter sites, and more pronounced following fire disturbances than in controls or those treated by woody plant removal.

Plant and Soil↗

USGS2023

Scenario-Based Decision Analysis: Integrated scenario planning and structured decision making for resource management under climate change

Managing resources under climate change is a high-stakes and daunting task, especially because climate change and associated complex biophysical responses engender sustained directional changes as well as abrupt transformations. This environmental non-stationarity challenges assumptions and expectations among scientists, managers, rights holders, and stakeholders. These challenges are anything but straightforward – a high degree of uncertainty impedes our ability to predict the environmental trajectory with confidence, and affected resources often span multiple governance jurisdictions or are subject to competing management objectives. Fortunately, tools exist to help grapple with such challenges. Two commonly used tools are scenario planning (SP) and structured decision making (SDM). SP is a well-established approach for assessing system response and facilitating decision making under a wide range of conditions that are uncertain and uncontrollable, such as those associated with adapting to climate change. However, SP lacks a defined structure for establishing objectives, quantifying tradeoffs, and evaluating the performance of candidate decisions to meet those objectives. SDM, on the other hand, is rooted in decision theory and focuses on explicit (often quantitative) assessment of the expected outcomes of choosing among a set of decision alternatives. SDM has been criticized for an inability to account for surprises and for imposing an overly narrow framing of problems to increase tractability. We discuss the strengths and limitations of SDM and SP as experienced through their application in various resource-management contexts, and then propose a new generalized framework – Scenario-Based Decision Analysis (SBDA) – that integrates these complementary approaches. SBDA structures resource management problems and solutions while considering uncertainties and surprises to inform resource management decision making.

Biological Conservation↗

USGS2011

Adaptive resource management and the value of information

The value of information is a general and broadly applicable concept that has been used for several decades to aid in making decisions in the face of uncertainty. Yet there are relatively few examples of its use in ecology and natural resources management, and almost none that are framed in terms of the future impacts of management decisions. In this paper we discuss the value of information in a context of adaptive management, in which actions are taken sequentially over a timeframe and both future resource conditions and residual uncertainties about resource responses are taken into account. Our objective is to derive the value of reducing or eliminating uncertainty in adaptive decision making. We describe several measures of the value of information, with each based on management objectives that are appropriate for adaptive management. We highlight some mathematical properties of these measures, discuss their geometries, and illustrate them with an example in natural resources management. Accounting for the value of information can help to inform decisions about whether and how much to monitor resource conditions through time.

Ecological Modelling↗

USGS2009

CO2 storage resources, reserves, and reserve growth: Toward a methodology for integrated assessment of the storage capacity of oil and gas reservoirs and saline formations

Geologically based methodologies to assess the possible volumes of subsurface CO 2 storage must apply clear and uniform definitions of resource and reserve concepts to each assessment unit (AU). Application of the current state of knowledge of geologic, hydrologic, geochemical, and geophysical parameters (contingencies) that control storage volume and injectivity allows definition of the contingent resource (CR) of storage. The parameters known with the greatest certainty are based on observations on known traps (KTs) within the AU that produced oil, gas, and water. The aggregate volume of KTs within an AU defines the most conservation volume of contingent resource. Application of the concept of reserve growth to CR volume provides a logical path for subsequent reevaluation of the total resource as knowledge of CO 2 storage processes increases during implementation of storage projects. Increased knowledge of storage performance over time will probably allow the volume of the contingent resource of storage to grow over time, although negative growth is possible.

Energy Procedia↗

USGS2020

Water balance as an indicator of natural resource condition: Case studies from Great Sand Dunes National Park and Preserve

Managing climate impacts to natural resources in protected areas can be hampered by lack of monitoring data, poor understanding of natural resource responses to climate, or lack of timely condition assessments that can inform management actions. Here we demonstrate the utility of water balance as a tool for understanding natural resource responses to climate by developing case studies focused on stream flow, vegetation production, and wildfire ignition at Great Sand Dunes National Park and Preserve (GSDNP), U.S.A. The efficacy of water balance to predict these responses stems from the explicit integration of climate with site conditions that modify the effects of climate. This in turn results in estimates of water availability, water use, and water need that are proximal drivers of aquatic and terrestrial natural resource conditions. The water balance model successfully forecasted stream flow (r 2 = 0.69, P < 0.001); determined the critical water needs for maintaining annual vegetation production in different vegetation types spanning a large environmental gradient (r 2 = 0.18–0.71); and predicted proportion of historic wildfire ignitions in forest (r 2 = 0.96–0.99) and non-forest (r 2 = 0.96–0.97) vegetation types. Collectively, these case studies demonstrate practical approaches to translate climate data into assessments of natural resource condition that inform long-term planning and near-term strategic actions needed for conservation of protected areas.

Great Sand Dunes National Park and Preserve↗

USGS2016

A method for examining the geospatial distribution of CO2 storage resources applied to the Pre-Punta Gorda Composite and Dollar Bay reservoirs of the South Florida Basin, U.S.A

This paper demonstrates geospatial modification of the USGS methodology for assessing geologic CO2 storage resources, and was applied to the Pre-Punta Gorda Composite and Dollar Bay reservoirs of the South Florida Basin. The study provides detailed evaluation of porous intervals within these reservoirs and utilizes GIS to evaluate the potential spatial distribution of reservoir parameters and volume of CO2 that can be stored. This study also shows that incorporating spatial variation of parameters using detailed and robust datasets may improve estimates of storage resources when compared to applying uniform values across the study area derived from small datasets, like many assessment methodologies. Geospatially derived estimates of storage resources presented here (Pre-Punta Gorda Composite = 105,570 MtCO2; Dollar Bay = 24,760 MtCO2) were greater than previous assessments, which was largely attributed to the fact that detailed evaluation of these reservoirs resulted in higher estimates of porosity and net-porous thickness, and areas of high porosity and thick net-porous intervals were incorporated into the model, likely increasing the calculated volume of storage space available for CO2 sequestration. The geospatial method for evaluating CO2 storage resources also provides the ability to identify areas that potentially contain higher volumes of storage resources, as well as areas that might be less favorable.

Florida↗