SEARCH · Geology Reports

Results for “Complexity”

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

SourceResearch connectionFrom yearThrough year

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

At least 1,261 records · Page 70Linked to original sources

USGS2001

Spatial paradigms of lotic diatom distribution: A landscape ecology perspective

Spatial distributional patterns of benthic diatoms and their relation to current velocity were investigated in an unshaded cobble-bottom reach of White Creek (Washington County, NY). On 27 August 1999, diatoms were sampled and current velocity and depth were measured on a regular square sampling grid with a grain size of 0.01 m2, interval of 0.5 m, and extent of 16 m2. The relative abundance of the 18 common diatom species enumerated in the 81 samples was subjected to detrended correspondence analysis (DCA). The first axis (DCA1) explained 51% of the variance in diatom data and separated the samples according to current regimes. The spatial autocorrelation of DCA1 sample scores in deposition and erosion regions of White Creek was determined by Moran's I statistic to indicate patch size. In White Creek the patch length of all diatom communities was more than 3.1 m, whereas the patch width was 1 m in the deposition region and 0.5 m in the erosion region. There were 5 dominant diatom taxa, Achnanthes minutissima Ku??tz. et vars, Fragilaria capucina Dezmazie??res et vars, F. crotonensis Kitt., Diatoma vulgaris Bory, and Synedra ulna (Nitz.) Ehr. et vars. The patch length of the dominant species varied from 1 to more than 4.1 m, whereas the patch width, if defined, was 0.5 m. Achnanthes minutissima and F. capucina, the two diatom species with the highest relative abundance, displayed spatially structured patches of low abundance and comparatively random patches of high abundance, suggesting broad scale abiotic control of species performance in low abundance regions and finer scale biotic control of high abundance areas. Another objective of this study was to test the hypothesis that higher current velocities, which generally impede immigration, would increase randomness and complexity (i.e. homogeneity of diatom distributional patterns). The spatial complexity in low versus high velocity transects was determined by calculating the respective fractal dimension (D) of DCA1 scores. D of DCA1 was higher in the higher current velocity transects, suggesting that spatial complexity and homogeneity of diatom communities increased in faster currents. Partial canonical correspondence analysis was conducted on diatom, environmental, and spatial data to assess how much of the variance in species distribution could be attributed to environmental (current velocity and depth) versus spatial factors. The variance of species data, explained by the environment (exclusively current velocity), was 38%; whereas space alone contributed only 10%, indicating that 1) current velocity was the major factor that controlled diatom distribution in streams and 2) there were other spatially dependent variables, most likely biotic, but their role in shaping diatom communities was minor.

Journal of Phycology↗

USGS2007

Analysis of Alaskan burn severity patterns using remotely sensed data

Wildland fire is the dominant large-scale disturbance mechanism in the Alaskan boreal forest, and it strongly influences forest structure and function. In this research, patterns of burn severity in the Alaskan boreal forest are characterised using 24 fires. First, the relationship between burn severity and area burned is quantified using a linear regression. Second, the spatial correlation of burn severity as a function of topography is modelled using a variogram analysis. Finally, the relationship between vegetation type and spatial patterns of burn severity is quantified using linear models where variograms account for spatial correlation. These results show that: 1) average burn severity increases with the natural logarithm of the area of the wildfire, 2) burn severity is more variable in topographically complex landscapes than in flat landscapes, and 3) there is a significant relationship between burn severity and vegetation type in flat landscapes but not in topographically complex landscapes. These results strengthen the argument that differential flammability of vegetation exists in some boreal landscapes of Alaska. Additionally, these results suggest that through feedbacks between vegetation and burn severity, the distribution of forest vegetation through time is likely more stable in flat terrain than it is in areas with more complex topography. ?? IAWF 2007.

International Journal of Wildland Fire↗

USGS2024

Fine-resolution land cover mapping over large and mountainous areas for Lāna‘i, Hawaii using posterior probabilities, and expert knowledge

The task of accurately mapping species-specific vegetation cover in remote and topographically complex regions like those found in Hawaiʻi presents unique challenges. This study leverages a machine learning approach to accurately classify vegetation into fine species-specific classes across the island of Lāna‘i, Hawaii, offering a novel methodology for tackling such challenges. Utilizing high-resolution WordView-2 satellite imagery, a neural network classifier and a custom lidar-based geometric correction, we introduced two new approaches to refine our high-resolution land cover classifications. This included the implementation of prior-based adjustments to class posterior probabilities to enhance land cover classification accuracy. Moreover, we developed mixed hierarchical classification maps that use class posterior probabilities to identify, at the pixel level, the finest land cover class that meets a user-defined confidence threshold. The resulting high-resolution land cover map for Lāna‘i captures the rich diversity and distribution of native and invasive plant species with high overall accuracy, generally exceeding 95%, based on independent ground control data. The capacity to produce wall-to-wall species-level vegetation maps provides a new window into monitoring vegetation dynamics on Lāna‘i and similarly remote and topographically complex regions, and contributes to our broader understanding of ecosystem responses to invasive species, climatic changes, and land management practices such as erosion and sediment control planning. Our approach offers a blueprint for similar efforts in other complex and remote ecosystems.

Hawaii↗

USGS2003

Evolution of trophic transmission in parasites: Why add intermediate hosts?

Although multihost complex life cycles (CLCs) are common in several distantly related groups of parasites, their evolution remains poorly understood. In this article, we argue that under particular circumstances, adding a second host to a single-host life cycle is likely to enhance transmission (i.e., reaching the target host). For instance, in several situations, the propagules of a parasite exploiting a predator species will achieve a higher host-finding success by encysting in a prey of the target predator than by other dispersal modes. In such a case, selection should favor the transition from a singleto a two-host life cycle that includes the prey species as an intermediate host. We use an optimality model to explore this idea, and we discuss it in relation to dispersal strategies known among free-living species, especially animal dispersal. The model found that selection favored a complex life cycle only if intermediate hosts were more abundant than definitive hosts. The selective value of a complex life cycle increased with predation rates by definitive hosts on intermediate hosts. In exploring trade-offs between transmission strategies, we found that more costly trade-offs made it more difficult to evolve a CLC while less costly trade-offs between traits could favor a mixed strategy.

American Naturalist↗

USGS2025

Seasonal movements and demographics of the endangered White River Spinedace to inform restoration and translocation

Objective Translocation is a tool being explored to restart extirpated populations or facilitate new populations of endangered spring-dependent fish populations. Our objective was to provide information on habitat requirements for endangered White River Spinedace Lepidomeda albivallis during all seasons of the year and the population demographics that are necessary to plan conservation translocations of this species Methods We tagged and released White River Spinedace with passive integrated transponders during four twice-a-year events. Fish were subsequently recaptured or detected on six passive antennas placed throughout the Flag Springs Complex, Nevada. We evaluated movement data to understand seasonal habitat use patterns, used a Barker model to estimate monthly survival rates, adjusted counts to account for capture probability and estimate abundance, and applied reverse-time mark–recapture models to estimate recruitment to 70 mm total length. Results White River Spinedace were more active but used similar habitats during spawning seasons than during nonspawning seasons. Median life expectancy was about 5 months after tagging, and only 1% of adult White River Spinedace survived 3–4 years posttagging. The estimated population size in the Flag Springs Complex during our sampling period (November 2020 to June 2022) was fewer than a thousand White River Spinedace, and this estimate has been steady or slightly increasing. Conclusions Complex spring habitats with water temperatures ranging about 13°C to 21°C that are free from piscivorous fish are appropriate for White River Spinedace. The White River Spinedace population at Flag Springs is small but stable or increasing in size.

Transactions of the American Fisheries Society↗

USGS2019

Context matters: Using reinforcement learning to develop human-readable, state-dependent outbreak response policies

The number of all possible epidemics of a given infectious disease that could occur on a given landscape is large for systems of real-world complexity. Furthermore, there is no guarantee that the control actions that are optimal, on average, over all possible epidemics are also best for each possible epidemic. Reinforcement learning (RL) has been used to develop machine-readable context-dependent solutions for complex problems with many possible realisations ranging from video-games to the game of Go. RL could be a valuable tool to generate context-dependent policies for outbreak response, though translating the resulting policies into simple rules that can be read and interpreted by human decision-makers remains a challenge. Here we illustrate the application of RL to the development of context-dependent outbreak response policies to minimise outbreaks of foot-and-mouth disease. We show that control based on the resulting context-dependent policies, which adapt interventions to the specific outbreak, result in smaller outbreaks than static policies. We further illustrate two approaches for translating the complex machine-readable policies into simple heuristics that can be evaluated by human decision-makers.

Philosophical Transactions of the Royal Society B:↗

USGS1999

XAFS measurements on zinc chloride aqueous solutions from ambient to supercritical conditions using the diamond anvil cell

The structure and bonding properties of metal complexes in subcritical and supercritical fluids are still largely unknown. Conventional high pressure and temperature cell designs impose considerable limitations on the pressure, temperature, and concentration of metal salts required for measurements on solutions under supercritical conditions. In this study, we demonstrate the first application of the diamond anvil cell, specially designed for x-ray absorption studies of first-row transition metal ions in supercritical fluids. Zn K-edge XAFS spectra were measured from aqueous solutions of 1-2 m ZnCl 2 and up to 6 m NaCl, at temperatures ranging from 25-660 °C and pressures up to 800 MPa. Our results indicate that the ZnCl 4 2- complex is predominant in the 1 m ZnCl 2 /6 m NaCl solution, while ZnCl 2 (H 2 O) 2 is similarly predominant in the 2 m ZnCl 2 solution, at all temperatures and pressures. The Zn-Cl bond length of both types of chlorozinc(II) complexes was found to decrease at a rate of about 0.01 Å/100 °C.

Journal of Synchrotron Radiation↗

USGS2025

Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands

1. Decomposition controls the release of carbon and nutrients from decaying plant litter into soils or the atmosphere. In most biomes decomposition rates can be accurately predicted with simple mathematical models, but these models have long under-predicted decomposition in globally- extensive drylands. 2. We posit that the exposed surface conditions characteristic of drylands makes litter decomposition uniquely subject to microsite-specific environmental controls and spatially-variable microbial communities. As such, decomposition in dryland ecosystems – which are characterized by extremes in temporal heterogeneity of climate conditions and spatial heterogeneity of vegetation cover with corresponding microclimate variability – is a prime example of a macrosystems process that can be addressed by merging field data with new predictive models operating across a hierarchical continuum of spatial scales and process resolutions. 3. A macrosystems approach offers promise to reconcile model-measurement discrepancies by integrating observations and experiments across multiple scales, from microsites (e.g., shrub sub-canopy or intercanopy) to regions (e.g., across a 100s of km2 study site with complex topography, precipitation, and temperature) and ultimately to a continental perspective (e.g., North American drylands). 4. Recent developments in technology and data availability position the scientific community to integrate lab, field, modeling, and remote sensing approaches across a hierarchical range of scales to capture the spatiotemporal distribution of litter and environmental conditions needed to predict decay dynamics at the micro-to-macroscale. This multi-scale approach promises a path forward to resolving a longstanding disconnect between measured and modeled data in dryland litter decomposition. 5. Dryland litter decomposition presents an excellent case study for resolving spatially and temporally complex biogeochemical dynamics through a hierarchical, multidisciplinary macrosystems approach. 6. We focus on dryland litter decomposition, but the hierarchical, multidisciplinary macrosystems approach we outline shows great potential for resolving other spatially and temporally complex biogeochemical processes across a wide range of ecosystems.

Functional Ecology↗

USGS2020

Hierarchical computing for hierarchical models in ecology

Bayesian hierarchical models allow ecologists to account for uncertainty and make inference at multiple scales. However, hierarchical models are often computationally intensive to fit, especially with large datasets, and researchers face trade-offs between capturing ecological complexity in statistical models and implementing these models. We present a recursive Bayesian computing (RB) method that can be used to fit Bayesian models efficiently in sequential MCMC stages to ease computation and streamline hierarchical inference. We also introduce transformation-assisted RB (TARB) to create unsupervised MCMC algorithms and improve interpretability of parameters. We demonstrate TARB by fitting a hierarchical animal movement model to obtain inference about individual- and population-level migratory characteristics. Our recursive procedure reduced computation time for fitting our hierarchical movement model by half compared to fitting the model with a single MCMC algorithm. We obtained the same inference fitting our model using TARB as we obtained fitting the model with a single algorithm. For complex ecological statistical models, like those for animal movement, multi-species systems, or large spatial and temporal scales, the computational demands of fitting models with conventional computing techniques can limit model specification, thus hindering scientific discovery. Transformation-assisted RB is one of the most accessible methods for reducing these limitations, enabling us to implement new statistical models and advance our understanding of complex ecological phenomena.

Article↗

USGS2024

Detecting stochasticity in population time series using a non-parametric test of intrinsic predictability

1. Many ecological systems dominated by stochastic dynamics can produce complex time series that inherently limit forecast accuracy. The ‘intrinsic predictability’ of these systems can be approximated by a time series complexity metric called weighted permutation entropy (WPE). While WPE is a useful metric to gauge forecast performance prior to model building, it is sensitive to noise and may be biased depending on the length of the time series. Here, we introduce a simple randomized permutation test (rWPE) to assess whether a time series is intrinsically more predictable than white noise. 2. We apply rWPE to both simulated and empirical data to assess its performance and usefulness. To do this, we simulate population dynamics under various scenarios, including a linear trend, chaotic, periodic and equilibrium dynamics. We further test this approach with observed abundance time series for 932 species across four orders of animals from the Global Population Dynamics Database. Finally, using Adélie ( Pygoscelis adeliae ) and emperor penguin ( Aptenodytes forsteri ) time series as case studies, we demonstrate the application of rWPE to multiple populations for a single species. 3. We show that rWPE can determine whether a system is significantly more predictable than white noise, even with time series as short as 10 years that show an apparent trend under biologically realistic stochasticity levels. Additionally, rWPE has statistical power close to 100% when time series are at least 30 time steps long and show chaotic or periodic dynamics. Power decreases to ~10% under equilibrium dynamics, irrespective of time series length. Among four classes of animal taxa, mammals have the highest relative frequency (28%) of time series that are both longer than 30 time steps and indistinguishable from white noise in terms of complexity, followed by insects (16%), birds (16%) and bony fishes (11%). 4. rWPE is a straightforward and useful method widely applicable to any time series, including short ones. By informing forecasters of the inherent limitations to a system's predictability, it can guide a modeller's expectations for forecast performance.

Methods in Ecology and Evolution↗

USGS2020

Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: ( i ) articulating alternative hypotheses; ( ii ) determining the magnitude of uncertainty regarding each hypothesis; ( iii ) evaluating the relevance of each hypothesis to acquisition decision‐making; and ( iv ) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Biological Reviews↗

USGS2015

Assessing the likely effectiveness of multispecies management for imperiled desert fishes with niche overlap analysis

A critical decision in species conservation is whether to target individual species or a complex of ecologically similar species. Management of multispecies complexes is likely to be most effective when species share similar distributions, threats, and response to threats. We used niche overlap analysis to assess ecological similarity of 3 sensitive desert fish species currently managed as an ecological complex. We measured the amount of shared distribution of multiple habitat and life history parameters between each pair of species. Habitat use and multiple life history parameters, including maximum body length, spawning temperature, and longevity, differed significantly among the 3 species. The differences in habitat use and life history parameters among the species suggest they are likely to respond differently to similar threats and that most management actions will not benefit all 3 species equally. Habitat restoration, frequency of stream dewatering, non-native species control, and management efforts in tributaries versus main stem rivers are all likely to impact each of the species differently. Our results demonstrate that niche overlap analysis provides a powerful tool for assessing the likely effectiveness of multispecies versus single-species conservation plans.

Conservation Biology↗

USGS2022

An introduction to decision science for conservation

Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science , decision theory , decision analysis , structured decision-making , and decision-support tools . Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.

Conservation Biology↗

USGS2021

Extrinsically reinforced hybrid speciation within Holarctic ermine (Mustela spp.) produces an insular endemic

Aim Refugial isolation during glaciation is an established driver of speciation; however, the opposing role of interglacial population expansion, secondary contact, and gene flow on the diversification process remains less understood. The consequences of glacial cycling on diversity are complex and especially so for archipelago species, which experience dramatic fluctuations in connectivity in response to both lower sea levels during glacial events and increased fragmentation during glacial recession. We test whether extended refugial isolation has led to the divergence of genetically and morphologically distinct species within Holarctic ermine ( Mustela erminea ), a small cosmopolitan carnivore species that harbours 34 extant subspecies, 14 of which are insular endemics. Location Holarctic. Methods We use genetic sequences (complete mitochondrial genomes, four nuclear genes) from >100 ermine (stoats) and geometric morphometric data for >200 individuals (27 of the 34 extant subspecies) from across their Holarctic range to provide an integrative perspective on diversification and endemism across this complex landscape. Multiple species delimitation methods ( iBPP , bPTP ) assessed congruence between morphometric and genetic data. Results Our results support the recognition of at least three species within the M. erminea complex, coincident with three of four genetic clades, tied to diversification in separate glacial refugia. We found substantial geographic variation within each species, with geometric morphometric results largely consistent with historical infraspecific taxonomy. Main conclusions Phylogeographic structure mirrors patterns of diversification in other Holarctic species, with a major Nearctic‐Palearctic split, but with greater intraspecific morphological diversity. Recognition of insular endemic species M. haidarum is consistent with a deep history of refugial persistence and highlights the urgency of mindful management of island populations along North America's North Pacific Coast. Significant environmental modification (e.g. industrial‐scale logging, mining) has been proposed for a number of these islands, which may elevate the risk of extinction of insular palaeoendemics.

Diversity and Distributions↗

USGS2015

Genetic diversity is related to climatic variation and vulnerability in threatened bull trout

Understanding how climatic variation influences ecological and evolutionary processes is crucial for informed conservation decision-making. Nevertheless, few studies have measured how climatic variation influences genetic diversity within populations or how genetic diversity is distributed across space relative to future climatic stress. Here, we tested whether patterns of genetic diversity (allelic richness) were related to climatic variation and habitat features in 130 bull trout ( Salvelinus confluentus ) populations from 24 watersheds (i.e., ~4–7th order river subbasins) across the Columbia River Basin, USA. We then determined whether bull trout genetic diversity was related to climate vulnerability at the watershed scale, which we quantified on the basis of exposure to future climatic conditions (projected scenarios for the 2040s) and existing habitat complexity. We found a strong gradient in genetic diversity in bull trout populations across the Columbia River Basin, where populations located in the most upstream headwater areas had the greatest genetic diversity. After accounting for spatial patterns with linear mixed models, allelic richness in bull trout populations was positively related to habitat patch size and complexity, and negatively related to maximum summer temperature and the frequency of winter flooding. These relationships strongly suggest that climatic variation influences evolutionary processes in this threatened species and that genetic diversity will likely decrease due to future climate change. Vulnerability at a watershed scale was negatively correlated with average genetic diversity ( r = −0.77; P < 0.001); watersheds containing populations with lower average genetic diversity generally had the lowest habitat complexity, warmest stream temperatures, and greatest frequency of winter flooding. Together, these findings have important conservation implications for bull trout and other imperiled species. Genetic diversity is already depressed where climatic vulnerability is highest; it will likely erode further in the very places where diversity may be most needed for future persistence.

Global Change Biology↗

USGS2010

Hydrological connectivity for riverine fish: measurement challenges and research opportunities

In this review, we first summarize how hydrologic connectivity has been studied for riverine fish capable of moving long distances, and then identify research opportunities that have clear conservation significance. Migratory species, such as anadromous salmonids, are good model organisms for understanding ecological connectivity in rivers because the spatial scale over which movements occur among freshwater habitats is large enough to be easily observed with available techniques; they are often economically or culturally valuable with habitats that can be easily fragmented by human activities; and they integrate landscape conditions from multiple surrounding catchment(s) with in‐river conditions. Studies have focussed on three themes: (i) relatively stable connections (connections controlled by processes that act over broad spatio‐temporal scales >1000 km 2 and >100 years); (ii) dynamic connections (connections controlled by processes acting over fine to moderate spatio‐temporal scales ∼1–1000 km 2 and <1–100 years); and (iii) anthropogenic influences on hydrologic connectivity, including actions that disrupt or enhance natural connections experienced by fish. We outline eight challenges to understanding the role of connectivity in riverine fish ecology, organized under three foci: (i) addressing the constraints of river structure; (ii) embracing temporal complexity in hydrologic connectivity; and (iii) managing connectivity for riverine fishes. Challenges include the spatial structure of stream networks, the force and direction of flow, scale‐dependence of connectivity, shifting boundaries, complexity of behaviour and life histories and quantifying anthropogenic influence on connectivity and aligning management goals. As we discuss each challenge, we summarize relevant approaches in the literature and provide additional suggestions for improving research and management of connectivity for riverine fishes. Specifically, we suggest that rapid advances are possible in the following arenas: (i) incorporating network structure and river discharge into analyses; (ii) increasing explicit consideration of temporal complexity and fish behaviour in the scope of analyses; and (iii) parsing degrees of human and natural influences on connectivity and defining acceptable alterations. Multiscale analyses are most likely to identify dominant patterns of connections and disconnections, and the appropriate scale at which to focus conservation activities.

Freshwater Biology↗

USGS2005

Predator functional response and prey survival: Direct and indirect interactions affecting a marked prey population

1. Predation plays an integral role in many community interactions, with the number of predators and the rate at which they consume prey (i.e. their functional response) determining interaction strengths. Owing to the difficulty of directly observing predation events, attempts to determine the functional response of predators in natural systems are limited. Determining the forms that predator functional responses take in complex systems is important in advancing understanding of community interactions. 2. Prey survival has a direct relationship to the functional response of their predators. We employed this relationship to estimate the functional response for bald eagle Haliaeetus leucocepalus predation of Canada goose Branta canadensis nests. We compared models that incorporated eagle abundance, nest abundance and alternative prey presence to determine the form of the functional response that best predicted intra-annual variation in survival of goose nests. 3. Eagle abundance, nest abundance and the availability of alternative prey were all related to predation rates of goose nests by eagles. There was a sigmoidal relationship between predation rate and prey abundance and prey switching occurred when alternative prey was present. In addition, predation by individual eagles increased as eagle abundance increased. 4. A complex set of interactions among the three species examined in this study determined survival rates of goose nests. Results show that eagle predation had both prey- and predator-dependent components with no support for ratio dependence. In addition, indirect interactions resulting from the availability of alternative prey had an important role in mediating the rate at which eagles depredated nests. As a result, much of the within-season variation in nest survival was due to changing availability of alternative prey consumed by eagles. 5. Empirical relationships drawn from ecological theory can be directly integrated into the estimation process to determine the mechanisms responsible for variation in observed survival rates. The relationship between predator functional response and prey survival offers a flexible and robust method to advance our understanding of predator-prey interactions in many complex natural systems where prey populations are marked and regularly visited. ?? 2006 British Ecological Society.

Journal of Animal Ecology↗

USGS2005

Comparison of an algebraic multigrid algorithm to two iterative solvers used for modeling ground water flow and transport

Numerical solution of large-scale ground water flow and transport problems is often constrained by the convergence behavior of the iterative solvers used to solve the resulting systems of equations. We demonstrate the ability of an algebraic multigrid algorithm (AMG) to efficiently solve the large, sparse systems of equations that result from computational models of ground water flow and transport in large and complex domains. Unlike geometric multigrid methods, this algorithm is applicable to problems in complex flow geometries, such as those encountered in pore-scale modeling of two-phase flow and transport. We integrated AMG into MODFLOW 2000 to compare two- and three-dimensional flow simulations using AMG to simulations using PCG2, a preconditioned conjugate gradient solver that uses the modified incomplete Cholesky preconditioner and is included with MODFLOW 2000. CPU times required for convergence with AMG were up to 140 times faster than those for PCG2. The cost of this increased speed was up to a nine-fold increase in required random access memory (RAM) for the three-dimensional problems and up to a four-fold increase in required RAM for the two-dimensional problems. We also compared two-dimensional numerical simulations of steady-state transport using AMG and the generalized minimum residual method with an incomplete LU-decomposition preconditioner. For these transport simulations, AMG yielded increased speeds of up to 17 times with only a 20% increase in required RAM. The ability of AMG to solve flow and transport problems in large, complex flow systems and its ready availability make it an ideal solver for use in both field-scale and pore-scale modeling.

Ground Water↗