Geology topics

Kimberly A. Jones

Publications and source records attributed to Kimberly A. Jones.

5 recordsLinked to original sources

USGS2014

Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale

We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R 2 for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive.

North Central Appalachians;Northeastern Highlands;↗

USGS2014

Development of a regionally consistent geospatial dataset of agricultural lands in the Upper Colorado River Basin, 2007-10

Irrigation in arid environments can alter the natural rate at which salts are dissolved and transported to streams. Irrigated agricultural lands are the major anthropogenic source of dissolved solids in the Upper Colorado River Basin (UCRB). Understanding the location, spatial distribution, and irrigation status of agricultural lands and the method used to deliver water to agricultural lands are important to help improve the understanding of agriculturally derived dissolved-solids loading to surface water in the UCRB. Irrigation status is the presence or absence of irrigation on an agricultural field during the selected growing season or seasons. Irrigation method is the system used to irrigate a field. Irrigation method can broadly be grouped into sprinkler or flood methods, although other techniques such as drip irrigation are used in the UCRB. Flood irrigation generally causes greater dissolved-solids loading to streams than sprinkler irrigation. Agricultural lands in the UCRB mapped by state agencies at varying spatial and temporal resolutions were assembled and edited to represent conditions in the UCRB between 2007 and 2010. Edits were based on examination of 1-meter resolution aerial imagery collected between 2009 and 2011. Remote sensing classification techniques were used to classify irrigation status for the June to September growing seasons between 2007 and 2010. The final dataset contains polygons representing approximately 1,759,900 acres of agricultural lands in the UCRB. Approximately 66 percent of the mapped agricultural lands were likely irrigated during the study period.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS2012

Comparison of stream invertebrate response models for bioassessment metric

We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R 2 from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R 2 values than RICHTOL for the two regions tested. Modeled O/E R 2 values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.

California, Oregon↗

USGS2010

Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US

The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metrics of biological condition such as richness, tolerance, percent predators, index of biotic integrity, functional species traits, or even ordination axes scores. Our primary intent was to determine if effective models could be developed using watershed characteristics of disturbance to predict macroinvertebrate metrics among disparate and widely separated ecoregions. We aggregated macroinvertebrate data from universities and state and federal agencies in order to assemble stream data sets of high enough density appropriate for modeling in three distinct ecoregions in Oregon and California. Extensive review and quality assurance of macroinvertebrate sampling protocols, laboratory subsample counts and taxonomic resolution was completed to assure data comparability. We used widely available digital coverages of land-use and land-cover data summarized at the watershed and riparian scale as explanatory variables to predict macroinvertebrate metrics commonly used by state resource managers to assess stream condition. The “best” multiple linear regression models from each region required only two or three explanatory variables to model macroinvertebrate metrics and explained 41–74% of the variation. In each region the best model contained some measure of urban and/or agricultural land-use, yet often the model was improved by including a natural explanatory variable such as mean annual precipitation or mean watershed slope. Two macroinvertebrate metrics were common among all three regions, the metric that summarizes the richness of tolerant macroinvertebrates (RICHTOL) and some form of EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness. Best models were developed for the same two invertebrate metrics even though the geographic regions reflect distinct differences in precipitation, geology, elevation, slope, population density, and land-use. With further development, models like these can be used to elicit better causal linkages to stream biological attributes or condition and can be used by researchers or managers to predict biological indicators of stream condition at unsampled sites.

Ecological Indicators↗

USGS2009

Federal standards and procedures for the National Watershed Boundary Dataset (WBD)

The Watershed Boundary Dataset (WBD) is a seamless, national hydrologic unit dataset developed using the guidelines and specifications outlined in this document. A hydrologic unit defines the areal extent of surface-water drainage to an outlet point on a dendritic stream network or to outlet points where the stream network is not dendritic. A hydrologic unit may represent all or only part of the total drainage area to the outlet point so that multiple hydrologic units may be required to define the entire drainage area for a given outlet. Hydrologic unit boundaries in the WBD are determined on the basis of topographic, hydrologic, and other relevant landscape characteristics without regard for administrative, political, or jurisdictional boundaries. The WBD seamlessly represents hydrologic units at six required and two optional hierarchical levels mapped at a minimum of 1:24,000-scale in the United States, except for in Hawaii, the Caribbean, and the Pacific Islands, which are at 1:25,000-scale, and in Alaska, where the data range from the minimum required 1:24,000-scale to 1:63,360-scale. Hydrologic units in the WBD provide a standardized base for water-resources organizations to locate, store, retrieve, and exchange hydrologic data; to index and inventory hydrologic data and information; to catalog water-data acquisition activities; and to use in a variety of other applications. The specifications and procedures established in this document are intended to provide guidelines and best practices to local, regional, and national partners for delineating and updating the hydrologic units of the WBD. Maintaining the WBD using consistent practices improves watershed management through efficient sharing of information and resources and by ensuring that digital geographic data can be used with other related geographic information system data. Edits and additions to the hydrologic units are reviewed against this specification prior to inclusion to the national WBD.

Techniques and Methods↗