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At least 1,045 records · Page 58Linked to original sources
USGS2015

Accuracy or precision: Implications of sample design and methodology on abundance estimation

Sampling by spatially replicated counts (point-count) is an increasingly popular method of estimating population size of organisms. Challenges exist when sampling by point-count method, and it is often impractical to sample entire area of interest and impossible to detect every individual present. Ecologists encounter logistical limitations that force them to sample either few large-sample units or many small sample-units, introducing biases to sample counts. We generated a computer environment and simulated sampling scenarios to test the role of number of samples, sample unit area, number of organisms, and distribution of organisms in the estimation of population sizes using N -mixture models. Many sample units of small area provided estimates that were consistently closer to true abundance than sample scenarios with few sample units of large area. However, sample scenarios with few sample units of large area provided more precise abundance estimates than abundance estimates derived from sample scenarios with many sample units of small area. It is important to consider accuracy and precision of abundance estimates during the sample design process with study goals and objectives fully recognized, although and with consequence, consideration of accuracy and precision of abundance estimates is often an afterthought that occurs during the data analysis process.

Ecological Modelling↗
USGS2006

A molecular dawn for biogeochemistry

Biogeochemistry is at the dawn of an era in which molecular advances enable the discovery of novel microorganisms having unforeseen metabolic capabilities, revealing new insight into the underlying processes regulating elemental cycles at local to global scales. Traditionally, biogeochemical inquiry began by studying a process of interest, and then focusing downward to uncover the microorganisms and metabolic pathways mediating that process. With the ability to sequence functional genes from the environment, molecular approaches now enable the flow of inquiry in the opposite direction. Here, we argue that a focus on functional genes, the microorganisms in which they reside, and the interaction of those organisms with the broader microbial community could transform our understanding of many globally important biogeochemical processes. ?? 2006 Elsevier Ltd. All rights reserved.

Trends in Ecology and Evolution↗
USGS2010

Sikuliqiruq: Ice dynamics of the Meade river - Arctic Alaska, from freezeup to breakup from time-series ground imagery

Ice formation and breakup on Arctic rivers strongly influence river flow, sedimentation, river ecology, winter travel, and subsistence fishing and hunting by Alaskan Natives. We use time-series ground imagery ofthe Meade River to examine the process at high temporal and spatial resolution. Freezeup from complete liquid cover to complete ice cover ofthe Meade River at Atqasuk, Alaska in the fall of 2008 occurred in less than three days between 28 September and 2 October 2008. Breakup in 2009 occurred in less than two hours between 23:47 UTC on 23 May 2009 and 01:27 UTC on 24 May 2009. All times in UTC. Breakup in 2009 and 2010 was ofthe thermal style in contrast to the mechanical style observed in 1966 and is consistent with a warming Arctic. ?? 2010 Taylor & Francis.

Polar Geography↗
USGS2021

Testing which axes of species differentiation underlie covariance of phylogeographic similarity among montane sedge species

Co‐distributed species may exhibit similar phylogeographic patterns due to shared environmental factors or discordant patterns attributed to the influence of species‐specific traits. Although either concordant or discordant patterns could occur due to chance, stark differences in key traits (e.g., dispersal ability) may readily explain differences between species. Multiple species’ attributes may affect genetic patterns, and it is difficult to isolate the contribution of each. Here we compare the relative importance of two attributes, range size and niche breadth, in shaping the spatial structure of genetic variation in four sedge species (genus Carex ) from the Rocky Mountains. Within two pairs of co‐distributed species, one species exhibits narrow niche breadth, while the other species has broad niche breadth. Furthermore, one pair of co‐distributed species has a large geographical distribution, while the other has a small distribution. The four species represent a natural experiment to tease apart how these attributes (i.e., range size and niche breadth) affect phylogeographic patterns. Investigations of genetic variation and structure revealed that range size, but not niche breadth, is related to spatial genetic covariation across species of montane sedges. Our study highlights how isolating key attributes across multiple species can inform their impact on processes driving intraspecific differentiation.

Molecular Ecology↗
USGS2020

Biogeography of fire regimes in western US conifer forests: A trait-based approach

Aim Functional traits are a critical link between species distributions and the ecosystem processes that structure those species’ niches. Concurrent increases in the availability of functional trait data and our ability to model species distributions present an opportunity to develop functional trait biogeography, i.e. the mapping of functional traits across space. Functional trait biogeography can improve process-based predictions about the resistance of certain species assemblages to changing environmental conditions across landscape scales. We illustrate this concept by developing the first trait-based, quantitative ranking of fire resistance (adult tree survival) in North American conifer species, and mapping that fire resistance across space. Location and Time period Western Continental United States, present-day. Major taxa studied 29 common conifer tree species. Methods We compiled six traits for each species: three relating to tree morphology and three relating to litter flammability. We combined these traits into a single fire resistance score, and used community-weighted averaging to estimate the fire resistance scores of different forest communities, using interpolated species distribution and relative abundance data. Results Species associated with historically frequent fire have high fire resistance scores (e.g., Pinus ponderosa), reflected by thick bark, tall crowns, and flammable litter. Species associated with subalpine or arid conditions have low fire resistance scores (e.g., Picea engelmannii and Pinus edulis), reflected by thin bark, short stature, poor self-pruning and low litter flammability. A map of forest community fire resistance across the western US reveals agreement with independent assessments of historical fire regimes, while also identifying areas where community-wide species traits may be mismatched with historical fire regimes. Main conclusions Quantifying the functional traits that confer resistance to tree-killing fire provides a direct link between ecosystem disturbance and community resistance. Understanding this link is critical to evaluating long-term resilience of different forest types under dynamic fire regimes. Our work represents the first known spatial representation of fire-resistance traits at a regional scale, and as such provides a link between functional traits and biogeography relevant to a critical ecosystem process.

Global Ecology and Biogeography↗
USGS2010

Modeling spatial variation in avian survival and residency probabilities

The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.

Ecology↗
USGS2013

The floodplain food web mosaic: a study of its importance to salmon and steelhead with implications for their recovery

Although numerous studies have attempted to place species of interest within the context of food webs, such efforts have generally occurred at small scales or disregard potentially important spatial heterogeneity. If food web approaches are to be employed to manage species, studies are needed that evaluate the multiple habitats and associated webs of interactions in which these species participate. Here, we quantify the food webs that sustain rearing salmon and steelhead within a floodplain landscape of the Methow River, Washington, USA, a location where restoration has been proposed to restore side channels in an attempt to recover anadromous fishes. We combined year-long measures of production, food demand, and diet composition for the fish assemblage with estimates of invertebrate prey productivity to quantify food webs within the main channel and five different, intact, side channels; ranging from channels that remained connected to the main channel at low flow to those reduced to floodplain ponds. Although we found that habitats within the floodplain had similar invertebrate prey production, these habitats hosted different local food webs. In the main channel, 95% of total prey consumption flowed to fishes that are not the target of proposed restoration. These fishes consumed 64% and 47% of the prey resources that were found to be important to fueling chinook and steelhead production in the main channel, respectively. Conversely, in side channels, a greater proportion of prey was consumed by anadromous salmonids. As a result, carrying capacity estimates based on food were 251% higher, on average, for anadromous salmonids in side channels than the main channel. However, salmon and steelhead production was generally well below estimated capacity in both the main and side channels, suggesting these habitats are under-seeded with respect to food, and that much larger populations could be supported. Overall, this study demonstrates that floodplain heterogeneity is associated with the occurrence of a mosaic of food webs, all of which were utilized by anadromous salmonids, and all of which may be important to their recovery and persistence. In the long term, these and other fishes would likely benefit from restoring the processes that maintain floodplain complexity.

Washington↗
USGS2006

Users' manual for the Hydroecological Integrity Assessment Process software (including the New Jersey Assessment Tools)

This manual is a user’s guide to four computer software tools that have been developed for the Hydroecological Integrity Assessment Process. The Hydroecological Integrity Assessment Process recognizes that streamflow is strongly related to many critical physiochemical components of rivers, such as dissolved oxygen, channel geomorphology, and water temperature, and can be considered a “master variable” that limits the disturbance, abundance, and diversity of many aquatic plant and animal species. Applying the Hydroecological Integrity Assessment Process involves four steps: (1) a hydrologic classification of relatively unmodified streams in a geographic area using long-term gage records and 171 ecologically relevant indices; (2) the identification of statistically significant, nonredundant, hydroecologically relevant indices associated with the five major flow components for each stream class; and (3) the development of a stream-classification tool and a hydrologic assessment tool. Four computer software tools have been developed.

Open-File Report↗
USGS2015

Sea-floor morphology and sedimentary environments in western Block Island Sound, offshore of Fishers Island, New York

Multibeam-bathymetric and sidescan-sonar data, collected by the National Oceanic and Atmospheric Administration in a 114-square-kilometer area of Block Island Sound, southeast of Fishers Island, New York, are combined with sediment samples and bottom photography collected by the U.S. Geological Survey from 36 stations in this area in order to interpret sea-floor features and sedimentary environments. These interpretations and datasets provide base maps for studies on benthic ecology and resource management. The geologic features and sedimentary environments on the sea floor are products of the area’s glacial history and modern processes. These features include bedrock, drumlins, boulders, cobbles, large current-scoured bathymetric depressions, obstacle marks, and glaciolacustrine sediments found in high-energy sedimentary environments of erosion or nondeposition; and sand waves and megaripples in sedimentary environments characterized by coarse-grained bedload transport. Trawl marks are preserved in lower energy environments of sorting and reworking. This report releases the multibeam-bathymetric, sidescan-sonar, sediment, and photographic data and interpretations of the features and sedimentary environments in Block Island Sound, offshore Fishers Island.

New York↗
USGS2009

Riparian and Associated Habitat Characteristics Related to Nutrient Concentrations and Biological Responses of Small Streams in Selected Agricultural Areas, United States, 2003-04

Physical factors, including both in-stream and riparian habitat characteristics that limit biomass or otherwise regulate aquatic biological condition, have been identified by previous studies. However, linking the ecological significance of nutrient enrichment to habitat or landscape factors that could allow for improved management of streams has proved to be a challenge in many regions, including agricultural landscapes, where many ecological stressors are strong and the variability among watersheds typically is large. Riparian and associated habitat characteristics were sampled once during 2003-04 for an intensive ecological and nutrients study of small perennial streams in five contrasting agricultural landscapes across the United States to determine how biological communities and ecosystem processes respond to varying levels of nutrient enrichment. Nutrient concentrations were determined in stream water at two different sampling times per site and biological samples were collected once per site near the time of habitat characterization. Data for 141 sampling sites were compiled, representing five study areas, located in parts of the Delmarva Peninsula (Delaware and Maryland), Georgia, Indiana, Ohio, Nebraska, and Washington. This report examines the available data for riparian and associated habitat characteristics to address questions related to study-unit contrasts, spatial scale-related differences, multivariate correlation structure, and bivariate relations between selected habitat characteristics and either stream nutrient conditions or biological responses. Riparian and associated habitat characteristics were summarized and categorized into 22 groups of habitat variables, with 11 groups representing land-use and land-cover characteristics and 11 groups representing other riparian or in-stream habitat characteristics. Principal components analysis was used to identify a reduced set of habitat variables that describe most of the variability among the sampled sites. The habitat characteristics sampled within the five study units were compared statistically. Bivariate correlations between riparian habitat variables and either nutrient-chemistry or biological-response variables were examined for all sites combined, and for sites within each study area. Nutrient concentrations were correlated with the extent of riparian cropland. For nitrogen species, these correlations were more frequently at the basin scale, whereas for phosphorus, they were about equally frequent at the segment and basin scales. Basin-level extents of riparian cropland and reach-level bank vegetative cover were correlated strongly with both total nitrogen and dissolved inorganic nitrogen (DIN) among multiple study areas, reflecting the importance of agricultural land-management and conservation practices for reducing nitrogen delivery from near-stream sources. When sites lacking segment-level wetlands were excluded, the negative correlation of riparian wetland extent with DIN among 49 sites was strong at the reach and segment levels. Riparian wetland vegetation thus may be removing dissolved nutrients from soil water and shallow groundwater passing through riparian zones. Other habitat variables that correlated strongly with nitrogen and phosphorus species included suspended sediment, light availability, and antecedent water temperature. Chlorophyll concentrations in seston were positively correlated with phosphorus concentrations for all sites combined. Benthic chlorophyll was correlated strongly with nutrient concentrations in only the Delmarva study area and only in fine-grained habitats. Current velocity or hydraulic scour could explain correlation patterns for benthic chlorophyll among Georgia sites, whereas chlorophyll in seston was correlated with antecedent water temperature among Washington and Delmarva sites. The lack of any consistent correlation pattern between habitat characteristics and organic material density (ash-free dry mass)

Scientific Investigations Report↗
USGS2017

Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales

Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern U.S. region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern U.S. region, leading to weak relationships between drivers and stoichiometry. Our results suggest ecological context mediates controls on lake nutrients and stoichiometry. Predicting stoichiometry was generally more difficult than predicting nutrient concentrations, but human activity may decouple N and P, leading to better prediction of N:P stoichiometry in regions with high anthropogenic activity.

Ecological Applications↗
USGS1986

The boundary model: A geographical analysis of design and conservation of nature reserves

It is widely recognised that nearly all parks and reserves are too small to protect their biological diversity. In response to this problem, we have been developing a multidisciplinary ‘boundary model’ that focuses upon the processes of exchange across the administrative edges of nature reserves. The model incorporates known dynamics from various disciplines and describes the interactions of these forces across the boundary. These disciplines include biogeography, ecology, and human effects, influences and attitudes in an understanding of reserve boundary vulnerability and effectiveness. The boundary model recognises the development of edges in association with the establishment of the administrative boundary. However, it discerns between ‘natural’ and ‘generated’ edges that are based upon the differing stimuli for their development and change. Segmentation of the boundary is recognised as a manifestation of environmental heterogeneity. The boundary model suggests that exposure of the reserve is a major determinate of potential vulnerability. Effectiveness of reserve protection is hypothesised to be more dependent upon what crosses the boundary than upon any internal processes alone.

Biological Conservation↗
USGS2015

Defining conservation targets on a landscape-scale

Conservation planning, the process of deciding how to protect, conserve, enhance and(or) minimize loss of natural and cultural resources, is a fundamental process to achieve conservation success in a time of rapid environmental change. Conservation targets, the measurable expressions of desired resource conditions, are an important tool in biological planning to achieve effective outcomes. Conservation targets provide a focus for planning, design, conservation action, and collaborative monitoring of environmental trends to guide landscape-scale conservation to improve the quality and quantity of key ecological and cultural resources. It is essential to have an iterative and inclusive method to define conservation targets that is replicable and allows for the evaluation of the effectiveness of conservation targets over time. In this document, we describe a process that can be implemented to achieve landscape-scale conservation, which includes defining conservation targets. We also describe what has been accomplished to date (September 2015) through this process for the Peninsular Florida Landscape Conservation Cooperative (PFLCC).

Florida↗
USGS2010

A counter-intuitive approach to calculating non-exchangeable 2 H isotopic composition of hair: treating the molar exchange fraction f E as a process-related rather than compound-specific variable

Hair is a keratinous tissue that incorporates hydrogen from material that an animal consumes but it is metabolically inert following synthesis. The stable hydrogen isotope composition of hair has been used in ecological studies to track migrations of mammals as well as for forensic and archaeological purposes to determine the provenance of human remains or the recent geographic life trajectory of living people. Measurement of the total hydrogen isotopic composition of a hair sample yields a composite value comprised of both metabolically informative, non-exchangeable hydrogen and exchangeable hydrogen, with the latter reflecting ambient or sample preparation conditions. Neither of these attributes is directly measurable, and the non-exchangeable hydrogen composition is obtained by estimation using a commonly applied mathematical expression incorporating sample measurements obtained from two distinct equilibration procedures. This commonly used approach treats the fraction of exchangeable hydrogen as a mixing ratio, with a minimal procedural fractionation factor assumed to be close or equal to 1. Instead, we propose to use full molar ratios to derive an expression for the non-exchangeable hydrogen composition explicitly as a function of both the procedural fractionation factor α and the molar hydrogen exchange fraction f E . We apply these derivations in a longitudinal study of a hair sample and demonstrate that the molar hydrogen exchange fraction f E should, like the procedural fractionation factor α, be treated as a process-dependent parameter, i.e. a reaction-specific constant. This is a counter-intuitive notion given that maximum theoretical values for the molar hydrogen exchange fraction f E can be calculated that are arguably protein-type specific and, as such, f E could be regarded as a compound-specific constant. We also make some additional suggestions for future approaches to determine the non-exchangeable hydrogen composition of hair and the use of standards.

Rapid Communications in Mass Spectrometry↗
USGS2012

Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example

Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.

Landscape Ecology↗
USGS2026

Incorporating location uncertainty improves inference with stop-level North American Breeding Bird Survey data

Ecological models should account for uncertainty to be most effective and useful. Yet, uncertainty from model covariates—unlike that from other sources, such as sampling error or process variability—is seldom explicitly incorporated. This can cause underestimates of uncertainty to cascade through model parameter estimates, predictions, and downstream uses. Burner et al. proposed a method for quantifying uncertainty in covariates and incorporating it into models using informative Bayesian priors. This method was applied to stop-level Breeding Bird Survey (BBS) analyses, where land cover uncertainty at each stop arises from substantial stop location uncertainty. A limited validation of model-estimated land cover, using stops with known locations, indicated the method’s potential effectiveness, but it was not rigorously evaluated. We conduct a robust simulation-based test, generating stop locations, extracting land cover, and simulating bird communities across 210 BBS routes in the upper Midwest. We compare 3 models: a “known” model with true land cover, a “naive” model assuming consistent 800-m stop spacing, and a “full” model using informative priors to estimate land cover. Species parameter estimates and predicted prevalence patterns across gradients in land cover from the full model approached those of the known model and were substantially closer to the true values used in simulations relative to those from the naive model. Naive model parameters were more biased relative to the other models, and credible intervals of predicted species prevalence rarely included the true simulated values. The full model also produced land cover covariate estimates closer to true simulation values relative to the mean informative priors. Our results show that, for the BBS, informative priors enable more accurate stop-level analyses despite location uncertainty. In contrast, naive models that ignore this uncertainty yield poor inferences. More broadly, we demonstrate empirically the utility of informative priors to account for covariate uncertainty in ecological models.

Michigan, Minnesota, Wisconson↗
USGS2024

Dust in the Critical Zone: North American case studies

The dust cycle facilitates the exchange of particles among Earth's major systems, enabling dust to traverse ecosystems, cross geographic boundaries, and even move uphill against the natural flow of gravity. Dust in the atmosphere is composed of a complex and ever-changing mixture that reflects the evolving human footprint on the landscape. The emission, transport, and deposition of dust interacts with and connects Critical Zone processes at all spatial and temporal scales. Landscape properties, land use, and climatic factors influence the wind erosion of soil and nutrient loss, which alters the long-term ecological dynamics at erosional locations. Once in the atmosphere, dust particles influence the amount of solar radiation reaching Earth, and interact with longwave (terrestrial) radiation, with cascading effects on the climate system. Finally, the wet and dry deposition of particles influences ecosystem structure, composition, and function over both short and long-term scales. Tracking dust particles from source to sink relies on monitoring and measurement of the geochemical composition and size distribution of the particles, space-borne and ground-based remote sensing, and dust modeling. Dust is linked to human systems via land use and policies that contribute to dust emissions and the health-related consequences of particulate loads and composition. Despite the significant influence dust has in shaping coupled natural-human systems, it has not been considered a key component of the Critical Zone. Here, we demonstrate that dust particles should be included as a key component of the Critical Zone by outlining how dust interacts with and shapes Earth System processes from generation, through transport, to deposition. We synthesize current understanding from global research and identify critical data and knowledge gaps while showcasing case studies from North America.

Earth-Science Reviews↗
USGS2003

Structural Equation Modeling: Applications in ecological and evolutionary biology

This book presents an introduction to the methodology of structural equation modeling, illustrates its use, and goes on to argue that it has revolutionary implications for the study of natural systems. A major theme of this book is that we have, up to this point, attempted to study systems primarily using methods (such as the univariate model) that were designed only for considering individual processes. Understanding systems requires the capacity to examine simultaneous influences and responses. Structural equation modeling (SEM) has such capabilities. It also possesses many other traits that add strength to its utility as a means of making scientific progress. In light of the capabilities of SEM, it can be argued that much of ecological theory is currently locked in an immature state that impairs its relevance. It is further argued that the principles of SEM are capable of leading to the development and evaluation of multivariate theories of the sort vitally needed for the conservation of natural systems. Supplementary information can be found at the authors website, http://www.jamesbgrace.com/ . • Details why multivariate analyses should be used to study ecological systems • Exposes unappreciated weakness in many current popular analyses • Emphasizes the future methodological developments needed to advance our understanding of ecological systems.

Book↗