Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Ecological Processes”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources
USGS2005

Effective discharge analysis of ecological processes in streams

Discharge is a master variable that controls many processes in stream ecosystems. However, there is uncertainty of which discharges are most important for driving particular ecological processes and thus how flow regime may influence entire stream ecosystems. Here the analytical method of effective discharge from fluvial geomorphology is used to analyze the interaction between frequency and magnitude of discharge events that drive organic matter transport, algal growth, nutrient retention, macroinvertebrate disturbance, and habitat availability. We quantify the ecological effective discharge using a synthesis of previously published studies and modeling from a range of study sites. An analytical expression is then developed for a particular case of ecological effective discharge and is used to explore how effective discharge varies within variable hydrologic regimes. Our results suggest that a range of discharges is important for different ecological processes in an individual stream. Discharges are not equally important; instead, effective discharge values exist that correspond to near modal flows and moderate floods for the variable sets examined. We suggest four types of ecological response to discharge variability: discharge as a transport mechanism, regulator of habitat, process modulator, and disturbance. Effective discharge analysis will perform well when there is a unique, essentially instantaneous relationship between discharge and an ecological process and poorly when effects of discharge are delayed or confounded by legacy effects. Despite some limitations the conceptual and analytical utility of the effective discharge analysis allows exploring general questions about how hydrologic variability influences various ecological processes in streams.

Water Resources Research↗
USGS2007

Living in the branches: Population dynamics and ecological processes in dendritic networks

Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.

Ecology Letters↗
USGS2007

Nutrient addition differentially affects ecological processes of Avicennia germinans in nitrogen versus phosphorus limited mangrove ecosystems

Nutrient over-enrichment is a major threat to marine environments, but system-specific attributes of coastal ecosystems may result in differences in their sensitivity and susceptibility to eutrophication. We used fertilization experiments in nitrogen (N)- and phosphorus (P)-limited mangrove forests to test the hypothesis that alleviating different kinds of nutrient limitation may have different effects on ecosystem structure and function in natural systems. We compared a broad range of ecological processes to determine if these systems have different thresholds where shifts might occur in nutrient limitation. Growth responses indicated N limitation in Avicennia germinans (black mangrove) forests in the Indian River Lagoon (IRL), Florida, and P limitation at Twin Cays, Belize. When nutrient deficiency was relieved, A. germinans grew out of its stunted form by increasing wood relative to leaf biomass and shoot length relative to lateral growth. At the P-limited site, P enrichment (+P) increased specific leaf area, N resorption, and P uptake, but had no effect on P resorption. At the N-limited site, +N increased both N and P resorption, but did not alter biomass allocation. Herbivory was greater at the P-limited site and was unaffected by +P, whereas +N led to increased herbivory at the N-limited site. The responses to nutrient enrichment depended on the ecological process and limiting nutrient and suggested that N- versus P-limited mangroves do have different thresholds. +P had a greater effect on more ecological processes at Twin Cays than did +N at the IRL, which indicated that the P-limited site was more sensitive to nutrient loading. Because of this sensitivity, eutrophication is more likely to cause a shift in nutrient limitation at P-limited Twin Cays than N-limited IRL. ?? 2007 Springer Science+Business Media, LLC.

Ecosystems↗
USGS2018

Monitoring dynamic spatio-temporal ecological processes optimally

Population dynamics vary in space and time. Survey designs that ignore these dynamics may be inefficient and fail to capture essential spatio‐temporal variability of a process. Alternatively, dynamic survey designs explicitly incorporate knowledge of ecological processes, the associated uncertainty in those processes, and can be optimized with respect to monitoring objectives. We describe a cohesive framework for monitoring a spreading population that explicitly links animal movement models with survey design and monitoring objectives. We apply the framework to develop an optimal survey design for sea otters in Glacier Bay. Sea otters were first detected in Glacier Bay in 1988 and have since increased in both abundance and distribution; abundance estimates increased from 5 otters to >5,000 otters, and they have spread faster than 2.7 km/yr. By explicitly linking animal movement models and survey design, we are able to reduce uncertainty associated with forecasting occupancy, abundance, and distribution compared to other potential random designs. The framework we describe is general, and we outline steps to applying it to novel systems and taxa.

Ecology↗
USGS2023

Bedform distributions and dynamics in a large, channelized river: Implications for benthic ecological processes

Sand bedforms are fundamental habitat elements for benthic fish in large, sand-bedded rivers and are hypothesized to provide flow refugia, food transport, and ecological disturbance. We explored bedform distributions and dynamics in the Lower Missouri River, Missouri, with the objective of understanding the implications of these features for benthic fish habitat, particularly for the endangered pallid sturgeon (Scaphirhynchus albus) and shovelnose sturgeon (Scaphirhynchus platorynchus) during their early life stages. We mapped bathymetry in a 3-kilometer-long reach of the highly engineered Lower Missouri River 22 times over a three-year period from 2019-2021 using a multibeam echosounder. Surveys included precise water surface and bed elevations over discharges ranging from 1,360-8,550 cubic meters per second. This included weekly surveys during a large flood event with a peak of 9,290 cubic meters per second in the spring and summer of 2019. Velocity was mapped with an acoustic Doppler current profiler during 11 of the 22 multibeam surveys. The dataset illustrates how bedforms are distributed in a typical Missouri River reach and how they evolve with changes in discharge. We measured a variety of bedform characteristics, including height, length, lee-slope angle, and crest orientation, and examined their relationship to larval sturgeon catch in the reach in 2020 and 2021. Bedform shapes are controlled by depositional environment and discharge and range in size from less than a meter in wavelength and amplitude to greater than 4 meters high and 75 meters long and generally have low angle lee-slopes. Small dunes were located in lower velocity regions on the inside of a bend and behind wing-dikes, as well as superimposed on larger dunes. Larger dunes were generally located in the channel thalweg and were associated with higher flow velocities. However, bedform size did not necessarily scale with discharge over the course of the 2019 flood, possibly due to sediment supply limitations and hysteresis effects. Changes in bedform size over the course of the flood event were most pronounced in the thalweg; less change in bedform size occurred behind wing dikes on the inside of channel bends, indicating some degree of habitat stability. Despite rarely getting caught in the thalweg, larval sturgeon drift in the thalweg until they are intercepted into off-channel habitats in wing dike fields, where they are caught in much higher numbers. Bedform orientations were affected by flow expansion around wing dikes, indicative of the role of wing dikes in influencing exchange of material between the thalweg and channel margins. Increased understanding of bedform distributions and dynamics will inform future sampling and habitat restoration designs for larval pallid sturgeon and contribute to increased understanding of their influence on benthic ecological processes.

Conference Paper↗
USGS2021

Cloud water interception in Hawai‘i: Developing capacity to characterize the spatial patterns and effects on water and ecological processes responses in Hawai‘i

Cloud-water interception (CWI) is the process by which fog or cloud water droplets are captured and accumulate on the leaves and branches of plants, some of which drips to the ground. Prior studies in Hawai'i indicate that CWI is highly variable and can contribute substantially to total precipitation. In this study, we monitored CWI and other processes at five mountain field sites on the Islands of Oʻahu, Maui, and Hawaiʻi to explore how CWI (1) varies with different climate and vegetation characteristics, (2) affects plant water use and growth, and (3) contributes to water resources. Results show that annual CWI varied from 158 to 910 mm, accounting for 3-34% of total water input at individual sites. This large variation was caused by differences in the quantity of cloud water, wind speed, and vegetation structure between sites. We developed a model to predict CWI using both climatic and forest canopy characteristics. On average, the model underestimated annual CWI by 18%, but reproduced the site differences relatively well. Plant water use decreased during periods of fog events mainly because of associated higher humidity. This new CWI model can be used to assess impacts of climate and land cover change on CWI and provide valuable information for resource management in Hawai‘i, which was not previously possible. At one field site, we explored the impacts of fog water on hydrological and ecological processes. Fog effects on native plant growth were indirect, primarily buffering effects of solar radiation. Removal of grass allowed natural regeneration of seedlings but did not alter soil moisture values. A soil data-collection program was initiated to help evaluate the role CWI has in providing moisture for plants, reducing wildfire risk within the fog zone, and contributing to groundwater recharge to aquifers that supply drinking water and groundwater discharge to streams.

Hawaii↗
USGS2019

oSCR: A spatial capture–recapture R package for inference about spatial ecological processes

Spatial capture–recapture (SCR) methods have become widely applied in ecology. The immediate adoption of SCR is due to the fact that it resolves some major criticisms of traditional capture–recapture methods related to heterogeneity in detectabililty, and the emergence of new technologies (e.g. camera traps, non‐invasive genetics) that have vastly improved our ability to collection spatially explicit observation data on individuals. However, the utility of SCR methods reaches far beyond simply convenience and data availability. SCR presents a formal statistical framework that can be used to test explicit hypotheses about core elements of population and landscape ecology, and has profound implications for how we study animal populations. In this software note, we describe the technical basis and analytical workflow of oSCR, an R package for analyzing spatial encounter history data using a multi‐session sex‐structured likelihood. The impetus for developing oSCR was to create an accessible and transparent analysis tool that allows users to conveniently and intuitively formulate statistical models that map directly to fundamental processes of interest in spatial population ecology (e.g. space use, resource selection, density and connectivity). We have placed an emphasis on creating a transparent and accessible code base that is coupled with a logical workflow that we hope stimulates active participation in further technical developments.

Ecography↗
USGS2004

Fire as an ecological process

This chapter investigates fire as a dynamic ecosystem process by first investigating fire in the context of general ecological theory, then discussing the concept of fire regimes, and finally by developing and applying a new framework for classifying fire regimes that better allows for the understanding of the patterns of fire as processes within ecosystems. Moreover, the chapter covers the succession theory and then proceeds through ecosystem, disturbance, and hierarchical theory. Next, it greatly expands on Agee’s (1993) treatment of conceptual distributions to include seven fire regime attributes, namely seasonality, fire return interval, fire size, spatial complexity, fireline intensity, fire severity, and fire type. Although humans have altered fire regimes throughout California for thousands of years, the pace of fire regime change has accelerated over the past 200 years. Recent and current management strategies have imposed directional changes on the pattern of fires in many California ecosystems.

California↗
USGS2013

Spatial ecological processes and local factors predict the distribution and abundance of spawning by steelhead ( Oncorhynchus mykiss ) across a complex riverscape

Processes that influence habitat selection in landscapes involve the interaction of habitat composition and configuration and are particularly important for species with complex life cycles. We assessed the relative influence of landscape spatial processes and local habitat characteristics on patterns in the distribution and abundance of spawning steelhead (Oncorhynchus mykiss), a threatened salmonid fish, across ~15,000 stream km in the John Day River basin, Oregon, USA. We used hurdle regression and a multi-model information theoretic approach to identify the relative importance of covariates representing key aspects of the steelhead life cycle (e.g., site access, spawning habitat quality, juvenile survival) at two spatial scales: within 2-km long survey reaches (local sites) and ecological neighborhoods (5 km) surrounding the local sites. Based on Akaike’s Information Criterion, models that included covariates describing ecological neighborhoods provided the best description of the distribution and abundance of steelhead spawning given the data. Among these covariates, our representation of offspring survival (growing-season-degree-days, °C) had the strongest effect size (7x) relative to other predictors. Predictive performances of model-averaged composite and neighborhood-only models were better than a site-only model based on both occurrence (percentage of sites correctly classified = 0.80±0.03 SD, 0.78±0.02 vs. 0.62±0.05, respectively) and counts (root mean square error = 3.37, 3.93 vs. 5.57, respectively). The importance of both temperature and stream flow for steelhead spawning suggest this species may be highly sensitive to impacts of land and water uses, and to projected climate impacts in the region and that landscape context, complementation, and connectivity will drive how this species responds to future environments.

Oregon↗
USGS2021

Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes

Regeneration is an essential demographic step that affects plant population persistence, recovery after disturbances, and potential migration to track suitable climate conditions. Challenges of restoring big sagebrush ( Artemisia tridentata ) after disturbances including fire-invasive annual grass interactions exemplify the need to understand the complex regeneration processes of this long-lived, woody species that is widespread across the semiarid western U.S. Projected 21st century climate change is expected to increase drought risks and intensify restoration challenges. A detailed understanding of regeneration will be crucial for developing management frameworks for the big sagebrush region in the 21st century. Here, we used two complementary models to explore spatial and temporal relationships in the potential of big sagebrush regeneration representing (1) range-wide big sagebrush regeneration responses in natural vegetation (process-based model) and (2) big sagebrush restoration seeding outcomes following fire in the Great Basin and the Snake River Plains (regression-based model). The process-based model suggested substantial geographic variation in long-term regeneration trajectories with central and northern areas of the big sagebrush region remaining climatically suitable, whereas marginal and southern areas are becoming less suitable. The regression-based model suggested, however, that restoration seeding may become increasingly more difficult, illustrating the particularly difficult challenge of promoting sagebrush establishment after wildfire in invaded landscapes. These results suggest that sustaining big sagebrush on the landscape throughout the 21st century may climatically be feasible for many areas and that uncertainty about the long-term sustainability of big sagebrush may be driven more by dynamics of biological invasions and wildfire than by uncertainty in climate change projections. Divergent projections of the two models under 21st century climate conditions encourage further study to evaluate potential benefits of re-creating conditions of uninvaded, unburned natural big sagebrush vegetation for post-fire restoration seeding, such as seeding in multiple years and, for at least much of the northern Great Basin and Snake River Plains, the control of the fire-invasive annual grass cycle.

Ecosphere↗
USGS2019

The rise of an apex predator following deglaciation

Aim Sea otters ( Enhydra lutris ) are an apex predator of the nearshore marine community and nearly went extinct at the turn of the 20th century. Reintroductions and legal protection allowed sea otters to re‐colonize much of their former range. Our objective was to chronicle the colonization of this apex predator in Glacier Bay, Alaska, to help understand the mechanisms that governed their successful colonization. Location Glacier Bay is a tidewater glacier fjord in southeastern Alaska that was entirely covered by glaciers in the mid‐18th century. Since then, it has endured the fastest tidewater glacier retreat in recorded history. Methods We collected and analysed several data sets, spanning 20 years, to document the spatio‐temporal dynamics of an apex predator expanding into an area where they were formerly absent. We used novel quantitative tools to model the occupancy, abundance and colonization dynamics of sea otters, while accounting for uncertainty in the data collection process, the ecological process and model parameters. Results Twenty years after sea otters were first observed colonizing Glacier Bay, they became one of the most abundant and widely distributed marine mammal. The population grew exponentially at a rate of 20% per year. They colonized Glacier Bay at a maximum rate of 6 km per year, with faster colonization rates occurring early in the colonization process. During colonization, sea otters selected shallow areas, close to shore, with a steep bottom slope, and a relatively simple shoreline complexity index. Main conclusions The growth and expansion of sea otters in Glacier Bay demonstrate how legal protection and translocation of apex predators can facilitate their successful establishment into a community in which they were formerly absent. The success of sea otters was, in part, a consequence of habitat that was left largely unperturbed by humans for the past 250 years. Further, sea otters and other marine predators, whose distribution is limited by ice, have the potential to expand in distribution and abundance, reshaping future marine communities in the wake of deglaciation and global loss of sea ice.

Alaska↗
USGS2016

Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.

Ecology and Evolution↗
USGS2023

A metasystem approach to designing environmental flows

Accelerating the design and implementation of environmental flows (e-flows) is essential to curb the rapid, ongoing loss of freshwater biodiversity and the benefits it provides to people. However, the effectiveness of e-flow programs may be limited by a singular focus on ensuring adequate flow conditions at local sites, which overlooks the role of other ecological processes. Recent advances in metasystem ecology have shown that biodiversity patterns and ecosystem functions across river networks result from the interplay of local (environmental filtering and biotic interactions) and regional (dispersal) ecological processes. No guidelines currently exist to account for these processes in designing e-flows. We address this gap by providing a step-by-step operational framework that outlines how e-flows can be designed to conserve or restore metasystem dynamics. Our recommendations are relevant to diverse regulatory contexts and can improve e-flow outcomes even in basins with limited in situ data.

BioScience↗
USGS2015

Suspended sediment transport trough a large fluvial-tidal channel network

The confluence of the Sacramento and San Joaquin Rivers, CA, forms a large network of interconnected channels, referred to as the Sacramento-San Joaquin Delta (the Delta). The Delta comprises the transition zone from the fluvial influences of the upstream rivers and tidal influences of San Francisco Bay downstream. Formerly an extensive tidal marsh, the hydrodynamics and geomorphology of Delta have been substantially modified by humans to support agriculture, navigation, and water supply. These modifications, including construction of new channels, diking and draining of tidal wetlands, dredging of navigation channels, and the operation of large pumping facilities for distribution of freshwater from the Delta to other parts of the state, have had a dramatic impact on the physical and ecological processes within the Delta. To better understand the current physical processes, and their linkages to ecological processes, the USGS maintains an extensive network of flow, sediment, and water quality gages in the Delta. Flow gaging is accomplished through use of the index-velocity method, and sediment monitoring uses turbidity as a surrogate for suspended-sediment concentration. Herein, we present analyses of the transport and dispersal of suspended sediment through the complex network of channels in the Delta. The primary source of sediment to the Delta is the Sacramento River, which delivers pulses of sediment primarily during winter and spring runoff events. Upon reaching the Delta, the sediment pulses move through the fluvial-tidal transition while also encountering numerous channel junctions as the Sacramento River branches into several distributary channels. The monitoring network allows us to track these pulses through the network and document the dominant transport pathways for suspended sediment. Further, the flow gaging allows for an assessment of the relative effects of advection (the fluvial signal) and dispersion (from the tides) on the sediment pulses as they move through the system. Herein, we present analyses of the “first flush” sediment pulse that occurred on the Sacramento River in December 2012, documenting the transport pathways as well as the effects of advection and dispersion on the sediment as it moved through the fluvial-tidal transition in the Delta. The analyses identified an important transport pathway through the interior of the Delta toward the large pumping facilities in the south Delta, which has important implications for native fish (because their movements are triggered by sediment/turbidity). The results also reveal the dramatic transition from fluvial-dominated transport (advection) to tidal-dominated transport (dispersion) as the sediment pulse approaches the estuary.

California↗
USGS2001

Coastal sage scrub case study

In ecological applications of large-scale spatial data to management decisions concerning land planning and conservation, errors and biases may creep into the analysis and decision making at several steps (see Chaps. 1, 2, and 3), including: • Uncertainty in positions of spatial locations of relevant ecological and physiographic features of the landscape. • Uncertainty of the type and attributes of land cover at a particular location. • Uncertainty in how different land covers at a position in space and the geometric arrangement of land covers nearby might influence an animal species occurrence or distribution, or the magnitude of some ecological process. • Uncertainty about the relative importance of each spatial location to the overall success or persistence of a population or ecological process. • Uncertainty about how to weight each species or ecological process in determining the overall biodiversity and functioning of ecosystems, local and national resource priorities, and consistency with legislative mandates. We would like to be able to quantify the errors at each step, identify biases, and pass these along to the next analysis step so that our degree of uncertainty regarding potential outcomes is evident at each level (e.g., Stoms et al. 1992).

Book chapter↗
USGS2019

Nonlinear reaction–diffusion process models improve inference for population dynamics

Partial differential equations (PDEs) are a useful tool for modeling spatiotemporal dynamics of ecological processes. However, as an ecological process evolves, we need statistical models that can adapt to changing dynamics as new data are collected. We developed a model that combines an ecological diffusion equation and logistic growth to characterize colonization processes of a population that establishes long-term equilibrium over a heterogeneous environment. We also developed a homogenization strategy to statistically upscale the PDE for faster computation and adopted a hierarchical framework to accommodate multiple data sources collected at different spatial scales. We highlighted the advantages of using a logistic reaction component instead of a Malthusian component when population growth demonstrates asymptotic behavior. As a case study, we demonstrated that our model improves spatiotemporal abundance forecasts of sea otters in Glacier Bay, Alaska. Furthermore, we predicted spatially varying local equilibrium abundances as a result of environmentally driven diffusion and density-regulated growth. Integrating equilibrium abundances over the study area in our application enabled us to infer the overall carrying capacity of sea otters in Glacier Bay, Alaska.

Alaska↗
USGS2003

A gentle introduction to quantile regression for ecologists

Quantile regression is a way to estimate the conditional quantiles of a response variable distribution in the linear model that provides a more complete view of possible causal relationships between variables in ecological processes. Typically, all the factors that affect ecological processes are not measured and included in the statistical models used to investigate relationships between variables associated with those processes. As a consequence, there may be a weak or no predictive relationship between the mean of the response variable ( y ) distribution and the measured predictive factors ( X ). Yet there may be stronger, useful predictive relationships with other parts of the response variable distribution. This primer relates quantile regression estimates to prediction intervals in parametric error distribution regression models (eg least squares), and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of the estimates for homogeneous and heterogeneous regression models.

Frontiers in Ecology and the Environment↗