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USGS2019

Bioclimatic envelopes for individual demographic events driven by extremes: Plant mortality from drought and warming

The occurrence of plant species across the globe is largely constrained by climate. Ecologists use plant-climate relationships such as bioclimatic envelopes and related niche models to determine potential environmental conditions promoting probable species occurrence. Traditionally bioclimatic envelopes either exclude disturbance explicitly, or only include disturbance as infrequent and smaller scale processes, assuming that the net effect of climate parameters on key demographic processes predict longer-term equilibrial responses of biota. Due to increasing frequency and extent of extreme events associated with climate change, ecologists may need to increase focus on individual demographic events driven by environmental extremes such as widespread coral bleaching or large-scale tree die-off. An expanded focus on how extreme events catalyze individual demographic events would complement existing tools that predict long-term equilibrial biogeographic responses associated with long-term trends in climate. In many cases, extreme conditions (e.g. drought) are a necessary precursor for an abrupt demographic event (e.g. large-scale tree die-off) and the effects of extremes can be exacerbated by climatic trends (e.g. higher temperatures in combination with drought). Here, we highlight application of bioclimatic models for predicting individual demographic events. Defining the environmental conditions that precipitate demographic events such as widespread tree mortality is a necessary precursor for applying predictions to geographic space, and may require challenging biota with experiments that impose a combination of ecologically extreme conditions in one parameter and a shifting distribution in another (e.g. drought under higher temperatures). Currently data on conditions that drive individual demographic events associated with extremes are usually rare, aggregated across time, and/or correlative. We highlight this approach with a case study of drought-induced mortality in adult Pinus edulis trees that predicts a more than five-fold increase in frequency of die-off events under a global change scenario of high emissions. This general approach complements both traditional bioclimatic envelopes and more detailed physiological approaches currently being refined to address climate change challenges. Notably, this proposed approach could be developed for any climate condition or plant life stage, offering promise for improving predictions of individual demographic events that are rapidly altering ecosystems globally.

International Journal of Plant Sciences↗

USGS2008

Overcompensatory response of a smallmouth bass (Micropterus dolomieu) population to harvest: Release from competition?

An intensive seven-year removal of adult, juvenile, and young-of-the-year smallmouth bass (Micropterus dolomieu) from a north temperate lake (Little Moose Lake, New York, USA) resulted in an increase in overall population abundance, primarily due to increased abundance of immature individuals. We developed a density-dependent, stage-structured model to examine conditions under which population control through harvest could result in the increase of a targeted species. Parameter values were derived from a 54-year data set collected from another north temperate lake (Lake Opeongo, Ontario, Canada) smallmouth bass population. Sensitivity analyses identified the demographic conditions that could lead to increased abundance in response to harvest. An increase in population abundance with harvest was most likely to occur when either (i) per capita recruitment at low levels of spawner abundance was large, juvenile survivorship was high, and maturation of age-4 and older juveniles was moderately high or (ii) per capita recruitment at low levels of spawner abundance was slightly lower, yet the maturation rate of age-3 juveniles and adult survivorship were high. Our modeling results together with empirical evidence further demonstrate the importance of overcompensation as a substantial factor to consider in efforts to regulate population abundance through harvest. ?? 2008 NRC.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2007

Terrestrial remote sensing science and algorithms planned for EOS/MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) will be the primary daily global monitoring sensor on the NASA Earth Observing System (EOS) satellites, scheduled for launch on the EOS-AM platform in June 1998 and the EOS-PM platform in December 2000. MODIS is a 36 channel radiometer covering 0·415-14·235 μm wavelengths, with spatial resolution from 250 m to 1 km at nadir. MODIS will be the primary EOS sensor for providing data on terrestrial biospheric dynamics and process activity. This paper presents the suite of global land products currently planned for EOSDIS implementation, to be developed by the authors of this paper, the MODIS land team (MODLAND). These include spectral albedo, land cover, spectral vegetation indices, snow and ice cover, surface temperature and fire, and a number of biophysical variables that will allow computation of global carbon cycles, hydrologic balances and biogeochemistry of critical greenhouse gases. Additionally, the regular global coverage of these variables will allow accurate surface change detection, a fundamental determinant of global change.

International Journal of Remote Sensing↗

USGS2002

A bibliography of terrain modeling (geomorphometry), the quantitative representation of topography: Supplement 4.0

Terrain modeling, the practice of ground-surface quantification, is an amalgam of Earth science, mathematics, engineering, and computer science. The discipline is known variously as geomorphometry (or simply morphometry), terrain analysis, and quantitative geomorphology. It continues to grow through myriad applications to hydrology, geohazards mapping, tectonics, sea-floor and planetary exploration, and other fields. Dating nominally to the co-founders of academic geography, Alexander von Humboldt (1808, 1817) and Carl Ritter (1826, 1828), the field was revolutionized late in the 20th Century by the computer manipulation of spatial arrays of terrain heights, or digital elevation models (DEMs), which can quantify and portray ground-surface form over large areas (Maune, 2001). Morphometric procedures are implemented routinely by commercial geographic information systems (GIS) as well as specialized software (Harvey and Eash, 1996; Köthe and others, 1996; ESRI, 1997; Drzewiecki et al., 1999; Dikau and Saurer, 1999; Djokic and Maidment, 2000; Wilson and Gallant, 2000; Breuer, 2001; Guth, 2001; Eastman, 2002). The new Earth Surface edition of the Journal of Geophysical Research, specializing in surficial processes, is the latest of many publication venues for terrain modeling. This is the fourth update of a bibliography and introduction to terrain modeling (Pike, 1993, 1995, 1996, 1999) designed to collect the diverse, scattered literature on surface measurement as a resource for the research community. The use of DEMs in science and technology continues to accelerate and diversify (Pike, 2000a). New work appears so frequently that a sampling must suffice to represent the vast literature. This report adds 1636 entries to the 4374 in the four earlier publications1. Forty-eight additional entries correct dead Internet links and other errors found in the prior listings. Chronicling the history of terrain modeling, many entries in this report predate the 1999 supplement. Coverage is representative from about 1800 through early–mid 2002. Papers increasingly are published exclusively or in duplicate on the Internet's World Wide Web; the dates given here for Web addresses (URLs) that lack a print publication indicate a Web site's last update or my last access of it. The bibliography is arranged alphabetically and thus is not readily summarized. This introduction cites about 500 entries, a third of them grouped under 24 morphometric topics, as a guide to the listing's contents. Continuing the practice of previous bibliographies in the series to provide more information on a few applications (see summary of past topics in Pike, 2000a), this report elaborates further on topographic data, putative new parameters, tectonic geomorphology/neo-orometry, biogeography, ice-cap morphometry, results from the Mars Global DEM, landslide-hazard mapping, terrain modeling as physics, Hack's law, and broad-scale computer visualization. The literature of some of these subjects is large, and none of the summaries is intended to more than introduce the topic and comment on some of the current contributions of terrain modeling. Closing the essay is a discussion of pre-1900 papers that trace the evolution of ridge-line and watercourse quantification by descriptive geometry, as well as comments on some new books and an on-line bulletin board.

Open-File Report↗

USGS2024

Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics

Invasive dreissenid mussels ( Dreissena polymorpha and Dreissena rostriformis bugensis ) have altered Great Lakes ecosystems through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict Dreissena spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with Dreissena spp. biomass. Point observations from the 2017 Lake Huron benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for in situ measurements of dreissenid presence and biomass at 119 sites across Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.

Lake Huron↗

USGS2013

Projected surface radiative forcing due to 2000--2050 land-cover land-use albedo change over the eastern United States

Satellite-derived contemporary land-cover land-use (LCLU) and albedo data and modeled future LCLU are used to study the impact of LCLU change from 2000 to 2050 on surface albedo and radiative forcing for 19 ecoregions in the eastern United States. The modeled 2000–2050 LCLU changes indicate a future decrease in both agriculture and forested land and an increase in developed land that induces ecoregion radiative forcings ranging from −0.175 to 0.432 W m −2 driven predominately by differences in the area and type of LCLU change. At the regional scale, these projected LCLU changes induce a net negative albedo decrease (−0.001) and a regional positive radiative forcing of 0.112 W m −2 . This overall positive forcing (i.e., warming) is almost 4 times greater than that estimated for documented 1973–2000 LCLU albedo change published in a previous study using the same methods.

Journal of Land Change Science↗

USGS2025

Combining acoustic telemetry and side-scan sonar to estimate abundance of endangered shortnose sturgeon in the Hudson River, New York

For endangered shortnose sturgeon (Acipenser brevirostrum), the ability to estimate and monitor population size is critical for tracking species’ recovery. Yet, contemporary abundance estimates have not been completed for many shortnose sturgeon populations, largely owing to the difficulty in using traditional abundance estimators for sturgeons. Here, we estimate the adult shortnose sturgeon population size of the Hudson River, NY by integrating data from two largely passive sampling methods – acoustic telemetry and side-scan sonar – into a Bayesian hierarchical model of abundance. We estimated the adult abundance to be 69,798 individuals (95% CI = 9,207-185,666), making the Hudson River the largest extant shortnose sturgeon population. Despite this, the population remains vulnerable to localized disturbances, as over 40% of the population congregated in a small overwintering habitat that coincides with an area of high anthropogenic activity. Accordingly, recurrent demographic surveys may be beneficial for gaining insight into the relative effects of anthropogenic and naturally stochastic processes shaping shortnose sturgeon demography. Our modeling framework provides a relatively low-cost alternative for future demographic monitoring of species of conservation concern.

New York↗

USGS1967

Climate and streamflow of Puerto Rico

The presently available data on streamflow, runoff rainfall, and temperature of Puerto Rico are evaluated, although the period of record is very short, with a view to contributing to the knowledge of hydrology of tropical islands. The average annual streamflow in Puerto Rico is 45 percent of the annual rainfall, or 15 percent more than in the eastern piedmont of the U.S. where it is 30 percent. Climate is assumed to be responsible for this difference as well as for the differences of the flows of Puerto Rican streams which vary from 15 to 85 percent of the annual rainfall. Variations in the climate of Puerto Rico are shown by Thornthwaite's climatic index on a map of the island, and the variations of the streamflow to rainfall ratios of Puerto Rican streams are shown to be related to Thornthwaite's climatic index.

Caribbean Journal of Science↗

USGS2018

Bipartite networks improve understanding of effects of waterbody size and angling method on angler–fish interactions

Networks used to study interactions could provide insights to fisheries. We compiled data from 27 297 interviews of anglers across waterbodies that ranged in size from 1 to 12 113 ha. Catch rates of fish species among anglers grouped by species targeted generally differed between angling methods (bank or boat). We constructed angler–catch bipartite networks (angling method specific) between anglers and fish and measured several network metrics. There was considerable variation in networks among waterbodies, with multiple metrics influenced by waterbody size. Number of species-targeting angler groups and number of fish species caught increased with increasing waterbody size. Mean number of links for species-targeting angler groups and fish species caught also increased with waterbody size. Connectance (realized proportion of possible links) of angler–catch interaction networks decreased slower for boat anglers than for bank anglers with increasing waterbody size. Network specialization (deviation of number of interactions from expected) was not significantly related to waterbody size or angling methods. Application of bipartite networks in fishery science requires careful interpretation of outputs, especially considering the numerous confounding factors prevalent in recreational fisheries.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2020

The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses

Hydrometeorologic monitoring networks are ubiquitous in contemporary earth-system science. Network stakeholders often inquire about the importance of sites and their locations when discussing funding and monitoring design. Support vector machines (SVMs) can be useful by their assigning each monitoring site as either a support or nonsupport vector. A potentiometric surface was created from synthetic data and 800 random observation locations (sites) as an analog to a groundwater-level network. Using generalized additive models for potentiometric surface prediction, simulations show that a subsample of support vectors from the 800 sites will out perform random samples of sample size equaling the support vector count. Support vector percentages from simulation quantify the recurrence that SVMs assign each site as a support vector, and these percentages in turn measure site importance. An example application of support vector percentages identifies important monitoring sites needed to regionalize the 0.1 annual exceedance probability peak streamflow. The results indicate that 152 of 283 streamgages with support vector percentages equalling 100 percent have not operated since about 2000 and generally have much smaller drainage areas than the greater streamgage network in Texas. The drainage area disparity is an indication of historical imbalance in peak streamflow data acquisition from various stream sizes in Texas.

Texas↗

USGS2021

Mean squared error, deconstructed

As science becomes increasingly cross-disciplinary and scientific models become increasingly cross-coupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model performance are “good” or “bad.” This apparent weakness has led to a myriad of specialized error metrics, which are sometimes aggregated to form a composite score. Such scores are inherently subjective, however, and while their components may be interpretable, the composite itself is not. We contend that, a better approach to model benchmarking and interpretation is to decompose MSE into interpretable components. To demonstrate the versatility of this approach, we outline some fundamental types of decomposition and apply them to predictions at 1,021 streamgages across the conterminous United States from three streamflow models. Through this demonstration, we hope to show that each component in a decomposition represents a distinct concept, like “season” or “variability,” and that simple decompositions can be combined to represent more complex concepts, like “seasonal variability,” creating an expressive language through which to interrogate models and data.

Journal of Advances in Earth Systems Modeling↗

USGS2016

Evaluation of gas production potential from gas hydrate deposits in National Petroleum Reserve Alaska using numerical simulations

An evaluation of the gas production potential of Sunlight Peak gas hydrate accumulation in the eastern portion of the National Petroleum Reserve Alaska (NPRA) of Alaska North Slope (ANS) is conducted using numerical simulations, as part of the U.S. Geological Survey (USGS) gas hydrate Life Cycle Assessment program. A field scale reservoir model for Sunlight Peak is developed using Advanced Processes & Thermal Reservoir Simulator (STARS) that approximates the production design and response of this gas hydrate field. The reservoir characterization is based on available structural maps and the seismic-derived hydrate saturation map of the study region. A 3D reservoir model, with heterogeneous distribution of the reservoir properties (such as porosity, permeability and vertical hydrate saturation), is developed by correlating the data from the Mount Elbert well logs. Production simulations showed that the Sunlight Peak prospect has the potential of producing 1.53 × 10 9 ST m 3 of gas in 30 years by depressurization with a peak production rate of around 19.4 × 10 4 ST m 3 /day through a single horizontal well. To determine the effect of uncertainty in reservoir properties on the gas production, an uncertainty analysis is carried out. It is observed that for the range of data considered, the overall cumulative production from the Sunlight Peak will always be within the range of ±4.6% error from the overall mean value of 1.43 × 10 9 ST m 3 . A sensitivity analysis study showed that the proximity of the reservoir from the base of permafrost and the base of hydrate stability zone (BHSZ) has significant effect on gas production rates. The gas production rates decrease with the increase in the depth of the permafrost and the depth of BHSZ. From the overall analysis of the results it is concluded that Sunlight Peak gas hydrate accumulation behaves differently than other Class III reservoirs (Class III reservoirs are composed of a single layer of hydrate with no underlying zone of mobile fluids) due to its smaller thickness and high angle of dip.

Alaska↗

USGS2020

Mapping fire regime ecoregions in California

The fire regime is a central framing concept in wildfire science and ecology and describes how a range of wildfire characteristics vary geographically over time. Understanding and mapping fire regimes is important for guiding appropriate management and risk reduction strategies and for informing research on drivers of global change and altered fire patterns. Most efforts to spatially delineate fire regimes have been conducted by identifying natural groupings of fire parameters based on available historical fire data. This can result in classes with similar fire characteristics but wide differences in ecosystem types. We took a different approach and defined fire regime ecoregions for California to better align with ecosystem types, without using fire as part of the definition. We used an unsupervised classification algorithm to segregate the state into spatial clusters based on distinctive biophysical and anthropogenic attributes that drive fire regimes – and then used historical fire data to evaluate the ecoregions. The fire regime ecoregion map corresponded well with the major land cover types of the state and provided clear separation of historical patterns in fire frequency and size, with lower variability in fire severity. This methodology could be used for mapping fire regimes in other regions with limited historical fire data or forecasting future fire regimes based on expected changes in biophysical characteristics.

California↗

USGS2013

Genetic population structure of muskellunge in the Great Lakes

We quantified genetic relationships among Muskellunge Esox masquinongy from 15 locations in the Great Lakes to determine the extent and distribution of measurable population structure and to identify appropriate spatial scales for fishery management and genetic conservation. We hypothesized that Muskellunge from each area represented genetically distinct populations, which would be evident from analyses of genotype data. A total of 691 Muskellunge were sampled ( n = 10–127/site) and genetic data were collected at 13 microsatellite loci. Results from a suite of analyses (including pairwise genetic differentiation, Bayesian admixture prediction, analysis of molecular variance, and tests of isolation by distance) indicated the presence of nine distinct genetic groups, including two that were approximately 50 km apart. Geographic proximity and low habitat complexity seemed to facilitate genetic similarity among areas, whereas Muskellunge from areas of greater habitat heterogeneity exhibited high differentiation. Muskellunge from most areas contained private alleles, and mean within-area genetic variation was similar to that reported for other freshwater fishes. Management programs aimed at conserving the broader diversity and long-term sustainability of Muskellunge could benefit by considering the genetically distinct groups as independent fisheries, and individual spawning and nursery habitats could subsequently be protected to conserve the evolutionary potential of Muskellunge.

Great Lakes↗

USGS2015

A comparison of survey methods for documenting presence of Myotis leibii (Eastern Small-Footed Bats) at roosting areas in Western Virginia

Many aspects of foraging and roosting habitat of Myotis leibii (Eastern Small-Footed Bat), an emergent rock roosting-obligate, are poorly described. Previous comparisons of effectiveness of acoustic sampling and mist-net captures have not included Eastern Small-Footed Bat. Habitat requirements of this species differ from congeners in the region, and it is unclear whether survey protocols developed for other species are applicable. Using data from three overlapping studies at two sampling sites in western Virginia’s central Appalachian Mountains, detection probabilities were examined for three survey methods (acoustic surveys with automated identification of calls, visual searches of rock crevices, and mist-netting) for use in the development of “best practices” for future surveys and monitoring. Observer effects were investigated using an expanded version of visual search data. Results suggested that acoustic surveys with automated call identification are not effective for documenting presence of Eastern Small-Footed Bats on talus slopes (basal detection rate of 0%) even when the species is known to be present. The broadband, high frequency echolocation calls emitted by Eastern Small-Footed Bat may be prone to attenuation by virtue of their high frequencies, and these factors, along with signal reflection, lower echolocation rates or possible misidentification to other bat species over talus slopes may all have contributed to poor acoustic survey success. Visual searches and mist-netting of emergent rock had basal detection probabilities of 91% and 75%, respectively. Success of visual searches varied among observers, but detection probability improved with practice. Additionally, visual searches were considerably more economical than mist-netting.

Virginia Journal of Science↗

USGS2015

Multiscale analysis of river networks using the R package linbin

Analytical tools are needed in riverine science and management to bridge the gap between GIS and statistical packages that were not designed for the directional and dendritic structure of streams. We introduce linbin, an R package developed for the analysis of riverscapes at multiple scales. With this software, riverine data on aquatic habitat and species distribution can be scaled and plotted automatically with respect to their position in the stream network or—in the case of temporal data—their position in time. The linbin package aggregates data into bins of different sizes as specified by the user. We provide case studies illustrating the use of the software for (1) exploring patterns at different scales by aggregating variables at a range of bin sizes, (2) comparing repeat observations by aggregating surveys into bins of common coverage, and (3) tailoring analysis to data with custom bin designs. Furthermore, we demonstrate the utility of linbin for summarizing patterns throughout an entire stream network, and we analyze the diel and seasonal movements of tagged fish past a stationary receiver to illustrate how linbin can be used with temporal data. In short, linbin enables more rapid analysis of complex data sets by fisheries managers and stream ecologists and can reveal underlying spatial and temporal patterns of fish distribution and habitat throughout a riverscape.

North American Journal of Fisheries Management↗

USGS2019

Regional patterns of anthropogenic influences on streams and rivers in the conterminous United States, from the early 1970s to 2012

This paper introduces a dataset containing consistent time-series measurements of anthropogenic activities potentially affecting stream quality across the conterminous United States and summarizes the most noteworthy trends from 61 variables in 16 categories. Data include measures of atmospheric deposition, agricultural production, livestock, urbanization, irrigation, land use, nutrients from fertilizer, dams/reservoirs, and pesticide use, among others. The trend periods range from 10 to 40 years, beginning as early as 1970 and ending in 2012. Detailed summaries are provided for 1992-2012. Key results include: increase of urbanization and ‘exurbanization’, particularly in the South, Southwest, and Mid-Atlantic; increases in crop production and fertilizer use in much of the Midwest; increases in the concentration of livestock, particularly of hogs and pigs; increases in irrigation, dams, and reservoirs in the Lower Mississippi and Lower Missouri watersheds, widespread increase in the use of the pesticide glyphosate; and widespread decrease in atmospheric deposition of sulfate. These results and others provide a framework for evaluating potential causes of water-quality changes over the past four decades.

Journal of Land Use Science↗

USGS2011

Episodic soil succession on basaltic lava fields in a cool, dry environment

Holocene- to late Pleistocene-aged lava flows at Craters of the Moon National Monument and Preserve provide an ideal setting to examine the early stages of soil formation under cool, dry conditions. Transects were used to characterize the amount and nature of soil cover on across basaltic lava flows ranging in age from 2.1 to 18.4 ka. Results indicate that on flows <13 ka, very shallow organic soils (Folists in Soil Taxonomy) are the dominant soil type, providing an areal coverage of up to &sim;25%. On flows ≥13.9 ka, deeper mineral soils including Entisols, Aridisols, and Mollisols become dominant and the areal extent increases to ≥95% on flows older than 18.4 ka. These data suggest there are two distinct pedogenic pathways associated with lava flows of the region. The first pathway is illustrated by the younger flows, where Folists dominate. In the absence of a major source of loess, relatively little mineral material accumulates and soils provide only minor coverage of the lava flows. Our results indicate that this pathway of soil development has not changed appreciably over the past &sim;10 ka. The second pedogenic pathway is illustrated by the flows older than 13.9 ka. These flows have been subject to deposition of large quantities of loess during and after the last regional glaciation, resulting in almost complete coverage. Subsequent pedogenesis has given rise to Aridisols and Mollisols with calcic and cambic horizons and mollic epipedons. This research highlights the importance of regional climate change on the evolution of Craters of the Moon soilscapes.

Idaho↗