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At least 469 records · Page 26Linked to original sources

USGS2017

Model-based estimators of density and connectivity to inform conservation of spatially structured populations

Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.

Ecosphere↗

USGS2017

Co-producing simulation models to inform resource management: a case study from southwest South Dakota

Simulation models can represent complexities of the real world and serve as virtual laboratories for asking “what if…?” questions about how systems might respond to different scenarios. However, simulation models have limited relevance to real-world applications when designed without input from people who could use the simulated scenarios to inform their decisions. Here, we report on a state-and-transition simulation model of vegetation dynamics that was coupled to a scenario planning process and co-produced by researchers, resource managers, local subject-matter experts, and climate change adaptation specialists to explore potential effects of climate scenarios and management alternatives on key resources in southwest South Dakota. Input from management partners and local experts was critical for representing key vegetation types, bison and cattle grazing, exotic plants, fire, and the effects of climate change and management on rangeland productivity and composition given the paucity of published data on many of these topics. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between grazer density and vegetation composition, as well as between the short- and long-term costs of invasive species management. It also pointed to impactful uncertainties related to the effects of fire and grazing on vegetation. More broadly, a scenario-based approach to model co-production bracketed the uncertainty associated with climate change and ensured that the most important (and impactful) uncertainties related to resource management were addressed. This cooperative study demonstrates six opportunities for scientists to engage users throughout the modeling process to improve model utility and relevance: (1) identifying focal dynamics and variables, (2) developing conceptual model(s), (3) parameterizing the simulation, (4) identifying relevant climate scenarios and management alternatives, (5) evaluating and refining the simulation, and (6) interpreting the results. We also reflect on lessons learned and offer several recommendations for future co-production efforts, with the aim of advancing the pursuit of usable science.

South Dakota↗

USGS2019

Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char

The success of species reintroductions can depend on a combination of environmental, demographic, and genetic factors. Although the importance of these factors in the success of reintroductions is well‐accepted, they are typically evaluated independently, which can miss important interactions. For species that persist in metapopulations, movement through and interaction with the landscape is predicted to be a vital component of persistence. Simulation‐based approaches are a promising technique for evaluating the independent and combined effects of these factors on the outcome of various reintroduction and associated management actions. We report results from a simulation study of bull trout ( Salvelinus confluentus ) reintroduction to three watersheds of the Pend Oreille River system in northeastern Washington State, USA. We used an individual‐based, spatially explicit simulation model to evaluate how reintroduction strategies, life history variation, and riverscape structure (e.g., network topology) interact to influence the demographic and genetic characteristics of reintroduced bull trout populations in three watersheds. Simulation scenarios included a range of initial genetic stocks (informed by empirical bull trout genetic data), variation in migratory tendency and life history, and two landscape connectivity alternatives representing a connected network (isolation‐by‐distance) and a fragmented network (isolation‐by‐barrier, using the known existing barriers). A novel feature of these simulations was the ability to consider the interaction of both demographic and genetic (i.e., demogenetic) factors in riverscapes with implicit asymmetric movement probabilities across the barriers. We found that connectivity (presence or absence of barriers) had the largest effect on demographic and genetic outcomes over 200 yr, with a greater effect than both initial genetic diversity and life history variation. We also identified regions of the study system in which bull trout populations persisted across a wide range of demographic, life history, and environmental connectivity parameters. Finally, we found no evidence that initial neutral genetic diversity influenced genetic diversity and structure after 200 yr; instead, genetic drift due to stray rate and population isolation dominated and erased any initial differences in genetic diversity. Our results highlight the utility of spatially explicit demogenetic approaches in exploring and understanding population dynamics—and their implications for management strategies—in fresh waters.

Washington↗

USGS2021

Integrated hierarchical models to inform management of transitional habitat and the recovery of a habitat specialist

Quantifying the contribution of habitat dynamics relative to intrinsic population processes in regulating species persistence remains an ongoing challenge in ecological and applied conservation. Understanding these drivers and their relationship is essential for managing habitat‐dependent species, especially those that specialize in transitional habitats. Limitations in the ability of natural disturbance to mediate transitional habitat dynamics have resulted in a decline in early‐ and mid‐successional vegetation structure and prompted the need for aggressive habitat management to replace natural perturbations and increase habitat structural complexity. We describe a collaborative effort with a group of independent land managers to design an adaptive management program for restoring an imperiled ecosystem and recovering declining populations of an endemic habitat specialist. We developed a set of integrated, hierarchical models to estimate management‐mediated transition rates among vegetation classes in two dominant scrub communities and the species response (local colonization and extinction probabilities) as a function of habitat state. Models were fit using a long‐term data set of habitat and occupancy observations from 361 Florida scrub‐jay territories across two Florida counties. Occupancy model results correspond closely to previous approaches of estimating differential survival and reproductive success associated with habitat conditions, with highest colonization and lowest extinction rates estimated for those habitat states found to have the highest rates of survival and reproduction. In addition to offering an innovative approach for jointly modeling habitat and species population dynamics, the program we describe will also be of interest from a management perspective by providing guidance for developing collaborative, adaptive management frameworks from the ground up. We engaged land managers via workshops to specify objectives and desired state‐variable conditions, identify management alternatives, and elicit consensus opinions on model parameters. Treating expert opinions as pseudo‐observations to define Dirichlet priors allowed us to make use of existing management knowledge. Formal learning was then accumulated by updating transition probability estimates as management activities were implemented over the study period. We believe this adaptive management framework provides a useful approach for increasing our understanding of complex ecological relationships and hope that it will be adopted by others who have interest in informing management and conservation efforts.

Florida↗

USGS2025

Too much and not enough data: Challenges and solutions for generating information in freshwater research and monitoring

Evaluating progress toward achieving freshwater conservation and sustainability goals requires transforming diverse types of data into useful information for scientists, managers, and other interest groups. Despite substantial increases in the volume of freshwater data collected worldwide, many regions and ecosystems still lack sufficient data collection and/or data access. We illustrate how these data challenges result from a diverse set of underlying mechanisms and propose solutions that can be applied by individuals or organizations. We discuss creative approaches to address data scarcity, including the use of community science, remote-sensing, environmental sensors, and legacy datasets. We highlight the importance of coordinated data collection efforts among groups and training programs to improve data access. At the institutional level, we emphasize the power of prioritizing data curation, incentivizing data publication, and promoting research that enhances data coverage and representativeness. Some of these strategies involve technological and analytical approaches, but many necessitate shifting the priorities and incentives of organizations such as academic and government research institutions, monitoring groups, journals, and funding agencies. Our overarching goal is to stimulate discussion to narrow the data disparities hindering the understanding of freshwater processes and their change across spatial scales.

Nahuel Huapi Lake, Lake Tahoe↗

USGS2025

Assessing the combined influence of biotic and anthropogenic stressors on polar bears to inform conservation planning

Developing conservation strategies for species vulnerable to the effects of climate change, like polar bears ( Ursus maritimus ), can be challenging given the uncertainty of future environmental conditions. Effective conservation planning requires identifying and ranking threats to the persistence of polar bears throughout their circumpolar range and then assessing the ability of mitigative actions to aid in meeting plan objectives. We used a Bayesian network model to (1) characterize the relative importance of multiple biotic and anthropogenic stressors on four ecoregional polar bear populations, at two future decadal time periods, and based on two Intergovernmental Panel on Climate Change (IPCC) greenhouse gas emissions scenarios (Shared Socioeconomic Pathways [SSPs] 2.6 [low] and 8.5 [high]); and (2) identify achievable management actions that may enhance the prospects of long-term persistence. Normative model runs indicated that populations in all four ecoregions incurred increasing probabilities of being decreased or greatly decreased over time. The probabilities of polar bear populations being decreased or greatly decreased from mid- to end of the century ranged from ~55% to 87% for the SSP 2.6 emissions scenario, and 82% to 94% for the SSP 8.5 emissions scenario among ecoregions. Arctic sea ice conditions and marine prey availability had the greatest influences on future polar bear population outcomes and overrode any relative influence from all other stressors. Hunting mortality was the most influential individual anthropogenic stressor in the Archipelago and Seasonal Ice Ecoregions, whereas terrestrial refugia quality grouped with various anthropogenic activities or factors (e.g., resource extraction, oil spill) was most influential for the Polar Basin Divergent Ice and Polar Basin Convergent Ice ecoregions. Our findings indicate that near-term proactive management of multiple anthropogenic stressors could cumulatively reduce the decline in populations such that if future sea ice habitat loss is eventually curtailed, population abundance would be greater than it would have been otherwise. Additionally, our findings suggest that there is value in tailoring management actions to address ecoregion-specific threats, which may prove useful in informing the development of future circumpolar conservation plans.

Ecosphere↗

USGS2014

Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach

The presence of endocrine-disrupting compounds (EDCs), particularly estrogenic compounds, in the environment has drawn public attention across the globe, yet a clear understanding of the extent and distribution of estrogenic EDCs in surface waters and their relationship to potential sources is lacking. The objective of the present study was to identify and examine the potential input of estrogenic EDC sources in North Carolina water bodies using a geographic information system (GIS) mapping and analysis approach. Existing data from state and federal agencies were used to create point and nonpoint source maps depicting the cumulative contribution of potential sources of estrogenic EDCs to North Carolina surface waters. Water was collected from 33 sites (12 associated with potential point sources, 12 associated with potential nonpoint sources, and 9 reference), to validate the predictive results of the GIS analysis. Estrogenicity (measured as 17β-estradiol equivalence) ranged from 0.06 ng/L to 56.9 ng/L. However, the majority of sites (88%) had water 17β-estradiol concentrations below 1 ng/L. Sites associated with point and nonpoint sources had significantly higher 17β-estradiol levels than reference sites. The results suggested that water 17β-estradiol was reflective of GIS predictions, confirming the relevance of landscape-level influences on water quality and validating the GIS approach to characterize such relationships.

Environmental Toxicology and Chemistry↗

USGS2019

Complexities, context, and new information about the Elwha River

Recently, Hand et al. (2018) discussed the socio- ecological complexities surround-ing natural resource policy, science, and management in the Columbia River Basin, using a case study of dam removal on the Elwha River in Washington State (WebFigure 1a). We feel compelled to provide additional historical context and correct some of the information provided by Hand et al. about the Elwha. The his-toric removals of the two Elwha River dams – a long- anticipated project that was decades in the making – have been touted by some as an environmental success story following the project’s completion in 2014. As with any complex endeavor, critical analyses and lessons learned continue to emerge, and will likely benefit future projects.

Washington↗

USGS2024

The value of information is context dependent: A demonstration of decision tools to address multispecies river temperature management under uncertainty

Trade-offs among objectives in natural resource management can be exacerbated in altered ecosystems and when there is uncertainty in predicted management outcomes. Multi-criteria decision analysis and value of information (VOI) are underutilized decision tools that can assist fisheries managers in handling trade-offs and evaluating the importance of uncertainty. We demonstrate the use of these tools using a case study in the Sacramento River, California, USA, where two imperiled species with different temperature requirements, winter-run Chinook Salmon Oncorhynchus tshawytscha and Green Sturgeon Acipenser medirostris , spawn and rear in the artificially cold Shasta Dam tailwater. A temperature-control device installed on Shasta Dam maintains cool water for Chinook Salmon; however, uncertainties exist related to the effects of temperatures on the spawning and rearing of both species. We consider four alternative hypotheses in models of early life-stage dynamics to evaluate the effects of alternative temperature management strategies on Chinook Salmon and Green Sturgeon management objectives. We used VOI to quantify the increase in management performance that can be expected by resolving hypothesis-based uncertainties as a function of the weight assigned to species-specific objectives. We found the decision was hindered by uncertainty; the best performing alternative depends on which hypothesis is true, with warmer or cooler alternative management strategies recommended when weights favor Green Sturgeon or Chinook Salmon objectives, respectively. The value of reducing uncertainty was highest when Green Sturgeon was slightly favored, highlighting the interaction between scientific uncertainty and decision makers' values. Our demonstration features multi-criteria decision analysis and VOI as transparent, deliberative tools that can assist fisheries managers in confronting value conflicts, prioritizing resolution of uncertainty, and optimally managing aquatic ecosystems.

Fisheries↗

USGS2020

Flow‐ecology modelling to inform reservoir releases for riparian restoration and management

Linked hydrologic, hydraulic, and ecological models can facilitate planning and implementing water releases from reservoirs to achieve ecological objectives along rivers. We applied a flow‐ecology model, the Ecosystem Functions Model (HEC‐EFM), to the Bill Williams River in southwestern USA to estimate areas suitable for recruitment of riparian tree seedlings in the context of managing flow releases from a large dam for riparian restoration. Ecological variables in the model included timing of seed dispersal, tolerable rates of flow recession, and tolerable duration of inundation following germination and early seedling establishment for native Fremont cottonwood and Goodding's willow, and non‐native tamarisk. Hydrological variables included peak flow timing, rate of flow recession following the peak, and duration of inundation. A one‐dimensional hydraulic model was applied to estimate stage‐discharge relationships along ~58 river kilometres. We then used HEC‐EFM to apply relationships between seedling ecology and streamflow to link hydrological dynamics with ecological response. We developed and validated HEC‐EFM based on an examination of seedling recruitment following an experimental flow release from Alamo Dam in spring 2006. The model predicted the largest area of potential recruitment for cottonwood (280–481 ha), with smaller areas predicted for willow (174–188 ha) and tamarisk (59–60 ha). Correlations between observed and predicted patches with successful seedling recruitment for areas within 40 m of the main channel ranged from 0.66 to 0.94. Finally, we examined arrays of hydrographs to identify which are most conducive to seedling recruitment along the river, given different combinations of peak flow, recession rate, and water volume released. Similar application of this model could be useful for informing reservoir management in the context of riparian restoration along other rivers facing similar challenges.

Arizona↗

USGS2016

Management decision making for fisher populations informed by occupancy modeling

Harvest data are often used by wildlife managers when setting harvest regulations for species because the data are regularly collected and do not require implementation of logistically and financially challenging studies to obtain the data. However, when harvest data are not available because an area had not previously supported a harvest season, alternative approaches are required to help inform management decision making. When distribution or density data are required across large areas, occupancy modeling is a useful approach, and under certain conditions, can be used as a surrogate for density. We collaborated with the New York State Department of Environmental Conservation (NYSDEC) to conduct a camera trapping study across a 70,096-km 2 region of southern New York in areas that were currently open to fisher ( Pekania [ Martes ] pennanti ) harvest and those that had been closed to harvest for approximately 65 years. We used detection–nondetection data at 826 sites to model occupancy as a function of site-level landscape characteristics while accounting for sampling variation. Fisher occupancy was influenced positively by the proportion of conifer and mixed-wood forest within a 15-km 2 grid cell and negatively associated with road density and the proportion of agriculture. Model-averaged predictions indicated high occupancy probabilities (>0.90) when road densities were low (<1 km/km 2 ) and coniferous and mixed forest proportions were high (>0.50). Predicted occupancy ranged 0.41–0.67 in wildlife management units (WMUs) currently open to trapping, which could be used to guide a minimum occupancy threshold for opening new areas to trapping seasons. There were 5 WMUs that had been closed to trapping but had an average predicted occupancy of 0.52 (0.07 SE), and above the threshold of 0.41. These areas are currently under consideration by NYSDEC for opening a conservative harvest season. We demonstrate the use of occupancy modeling as an aid to management decision making when harvest-related data are unavailable and when budgetary constraints do not allow for capture–recapture studies to directly estimate density.

Journal of Wildlife Management↗

USGS2022

Using surrogate taxa to inform response methods for invasive Grass Carp in the Laurentian Great Lakes

Sampling method decisions are critical for the effective monitoring and management of fisheries. Deploying the most effective sampling methodologies is particularly important when responding to new invasive species, where early response efforts have the best chances for eradication. In the Laurentian Great Lakes, the invasive Grass Carp Ctenopharyngodon idella is sampled using boat electrofishing and the combination method of boat electrofishing within and around a trammel net enclosure. We conducted a field study to compare the effectiveness of the two methods. We used capture data for surrogate taxa (i.e., Common Carp Cyprinus carpio and buffalo Ictiobus spp.) to compare the two methods because few Grass Carp were collected during the study. The sampling methods were compared within an occupancy modeling framework using an information-criteria model selection approach to evaluate seven alternative models. The base model included sampling method, year, water temperature, and sampling effort as covariates in the detection submodel and assumed that occupancy probability was constant across sites. The other six models built on the base model by including site, water body type (i.e., lentic vs. lotic), and interaction covariates in the detection submodel. The top-performing model, built on the base model, accounted for the influence of water body type and assumed the exchangeability of site effects in the detection submodel. The results indicated that the detection probabilities for both taxa were higher for the combination method than for boat electrofishing, with a median estimated difference in detection probability between the two methods of 0.11 (95% CI: 0.04–0.22) for Common Carp and 0.18 (95% CI: 0.08–0.28) for buffalo. Given that the combination method was more effective for detecting the surrogate taxa, we expect the combination method may be preferable to only boat electrofishing for Grass Carp removal.

Michigan, New York, Ohio, Ontario, Pennsylvania↗

USGS2023

Imperfect detection and misidentification affect inferences from data informing water operation decisions

Objective Managers can modify river flow regimes using fish monitoring data to minimize impacts from water management infrastructure. For example, operation of the gate-controlled Delta Cross Channel (DCC) in California can negatively affect the endangered Sacramento River winter-run Chinook Salmon Oncorhynchus tshawytscha . Although guidelines have been developed for DCC operations by using real-time juvenile fish sampling count data, there is uncertainty about how environmental conditions influence fish occupancy and the extent to which those relationships are affected by sampling and identification error. Methods We evaluated the effect of environmental conditions, imperfect detection, and misidentification error on salmon occupancy by analyzing data using hierarchical multistate occupancy models. A total of 14,147 trawl tows and beach seine hauls were conducted on 1058 sampling days between October and December from 1996 to 2019. During these surveys, 2803 juvenile winter-run Chinook Salmon were identified, and approximately 29% of the sampling days had at least one winter-run juvenile detected. Result The probability of misidentifying an individual juvenile winter-run Chinook Salmon in the field was estimated to be 0.056 based on fish identification examinations and genetic sampling. Occupancy varied considerably and was related to flow characteristics, water clarity, weather, time of year, and whether occupancy was detected during the previous sampling day. However, these relationships and their significance changed considerably when accounting for imperfect detection and the probability of misidentifying individual juvenile salmon. Detection was <0.3 under average sampling conditions during a single sample and was influenced by flow, water clarity, site, and volume sampled. Conclusion Our modeling results indicate that DCC gate closure decisions could occur on fewer days when imperfect detection and misidentification error are not accounted for. These findings demonstrate the need to account for identification and detection error while using monitoring data to assess factors influencing fish occupancy and inform future management decisions.

North American Journal of Fisheries Management↗

USGS2011

A geographic information system tool for aquatic resource conservation in the Red and Sabine River Watersheds of the southeast United States

Our goal was to build a geographic information system (GIS) tool to enhance modeling and hypothesis testing relevant to watersheds and fish fauna of the Red and Sabine Rivers in the southeastern United States. Species of concern were identified from wildlife action plans and Web sites. Spatial distributions of fish species and mercury in fillets were delineated using data from states. Public georeferenced data were obtained on land cover, soil type, forest canopy, impervious surfaces, wastewater facilities and 303(d) impaired waters. Overlay maps highlighted patterns across 8-digit hydrologic unit codes (HUCs). Bossier City, Louisiana and Beaumont, Texas areas displayed impervious surfaces over 10% and 303(d) waters per HUC were 20% and 8%, respectively. Because bowfin (Amia calva) (n=299) and bass (Micropterus spp.) (n=1493) occurred in up to 44% of HUCs and fillets contained elemental mercury concentrations across ranges monitored, they were appropriate indicators of bioavailable mercury. Of the total fish number showing >0.5ppm, 81% of records were derived from bowfin and bass, and stepwise multiple linear regressions indicated fish with mercury at these concentrations correlated with environmental variables. Detrended correspondence analysis showed total species occurrence and environmental relationships significant, where 81.6% of the variability in fish occurrence was explained by impervious surface, land cover other than canopy or impervious surface (such as wetlands and agricultural area) and canopy (forest type). Two-way indicator species analysis delineated species co-occurrence in HUCs (14 groups) and similarity of species composition (nine groups). Results identified three HUC groupings as potential targets for managerial interest. Quality control concerns for GIS development included site name data and priority rankings of critical fish species. This tool can be used to support modeling and trend analyses for several purposes, such as those relevant for developing and reporting on water quality standards and critical habitat assessments.

Arkansas, Louisiana, Oklahoma, Texas↗

USGS2016

Informing watershed connectivity barrier prioritization decisions: A synthesis

Water resources and transportation infrastructure such as dams and culverts provide countless socio-economic benefits; however, this infrastructure can also disconnect the movement of organisms, sediment, and water through river ecosystems. Trade-offs associated with these competing costs and benefits occur globally, with applications in barrier addition (e.g. dam and road construction), reengineering (e.g. culvert repair), and removal (e.g. dam removal and aging infrastructure). Barrier prioritization provides a unique opportunity to: (i) restore and reconnect potentially large habitat patches quickly and effectively and (ii) avoid impacts prior to occurrence in line with the mitigation hierarchy (i.e. avoid then minimize then mitigate). This paper synthesizes 46 watershed-scale barrier planning studies and presents a procedure to guide barrier prioritization associated with connectivity for aquatic organisms. We focus on practical issues informing prioritization studies such as available data sets, methods, techniques, and tools. We conclude with a discussion of emerging trends and issues in barrier prioritization and key opportunities for enhancing the body of knowledge.

River Research and Applications↗

USGS2025

Evaluation of juvenile salmon behavior to inform downstream fish passage development at a high head dam

F ish passage development is a priority at Tieton Dam, on the Tieton River in Washington state, because passage options were not included when the dam was constructed nearly 100 years ago. To inform downstream passage design, we conducted a study to evaluate migration and near-dam behavior of juvenile salmon. The primary goal of the study was to determine how fish approached the dam and to identify areas where they congregated. In its current configuration, water is passed through a deep intake located approximately 548 m upstream of the dam, so there was interest in determining if juvenile salmon spent more time near the intake or at the dam. We found that tagged fish primarily entered the dam forebay offshore and arrived at the dam near the spillway on the left bank of the reservoir. Tagged fish had extended residence times in the forebay and moved repeatedly between the intake and the dam. Using thermal profile data, we inferred that juvenile salmon likely occupied the upper 5 m of the water column during May and June before moving to deeper portions of the water column (10–27 m) during July–September when the reservoir became thermally stratified. We found that a small percentage of tagged fish passed the dam when the reservoir was rapidly drawn down during August–October, but additional research may be needed to fully assess entrainment risk through the intake. These findings suggest that downstream fish passage could be developed at Tieton Dam with a high probability of success, given that most fish survived reservoir passage and spent considerable time near the dam where they would be available to discover and utilize new passage routes.

Washington↗

USGS2018

GNIS-LD: Serving and visualizing the Geographic Names Information System Gazetteer as linked data

In this dataset description paper we introduce the GNIS-LD, an authoritative and public domain Linked Dataset derived from the Geographic Names Information System (GNIS) which was developed by the U.S. Geological Survey (USGS) and the U.S. Board on Geographic Names. GNIS provides data about current, as well as historical, physical, and cultural geographic features in the United States. We describe the dataset, introduce an ontology for geographic feature types, and demonstrate the utility of recent linked geographic data contributions made in conjunction with the development of this resource. Co-reference resolution links to GeoNames.org and DBpedia are provided in the form of owl:sameAs relations. Finally, we point out how the adapted workflow is foundational for complex Digital Line Graph (DLG) data from the USGS National Map and how the GNIS-LD data can be integrated with DLG and other data sources such as sensor observations.

Conference Paper↗

USGS1988

Knowledge-based geographic information systems (KBGIS): New analytic and data management tools

In its simplest form, a geographic information system (GIS) may be viewed as a data base management system in which most of the data are spatially indexed, and upon which sets of procedures operate to answer queries about spatial entities represented in the data base. Utilization of artificial intelligence (AI) techniques can enhance greatly the capabilities of a GIS, particularly in handling very large, diverse data bases involved in the earth sciences. A KBGIS has been developed by the U.S. Geological Survey which incorporates AI techniques such as learning, expert systems, new data representation, and more. The system, which will be developed further and applied, is a prototype of the next generation of GIS's, an intelligent GIS, as well as an example of a general-purpose intelligent data handling system. The paper provides a description of KBGIS and its application, as well as the AI techniques involved. ?? 1988 International Association for Mathematical Geology.

Mathematical Geology↗