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At least 595 records · Page 33Linked to original sources
USGS2025

Temporal and spatial equivalence in demographic responses of emperor penguins (Aptenodytes forsteri) to environmental change

1. Population ecology and biogeography applications often necessitate the transfer of models across spatial and/or temporal dimensions to make predictions outside the bounds of the data used for model fitting. However, ecological data are often spatiotemporally unbalanced such that the spatial or the temporal dimension tends to contain more data than the other. This unbalance frequently leads model transfers to become substitutions, which are predictions to a different dimension than the predictive model was built on. Despite the prevalence of substitutions in ecology, studies validating their performance and their underlying assumptions are scarce. 2. Here, we present a successful case study demonstrating both space-for-time and time-for-space substitutions using emperor penguins (Aptenodytes forsteri) as the focal species. Using abundance-based species distribution models (aSDM) of adult emperor penguins in attendance during spring across 50 colonies, we predict long-term annual fluctuations in fledgling abundance and breeding success at a single colony, Pointe Géologie. Subsequently, we construct statistical models from time series of extended counts on Pointe Géologie to predict average fledgling abundance across 50 colonies. 3. Our analysis reveals that distance to nearest open water (NOW) exhibits the strongest association with both temporal and spatial data. aSDM’s space-for-time substitution performance, as measured by Pearson correlation coefficient was 0.63 and 0.56 when predicting breeding success and fledgling abundance time series, respectively. Linear regression of fledgling abundance on NOW yields similar time-for-space substitution performance when predicting abundance distribution of emperor penguin colonies with a correlation coefficient of 0.58. 4. We posit that such space-time equivalence arises because: 1) emperor penguins colonies conform to their existing fundamental niche; 2) there is not yet any environmental novelty when comparing the spatial vs temporal variation of distance to nearest open water; and 3) models of more specific components of life histories, such as fledgling abundance, rather than occurrence or total population abundance, are more transferable. Identifying these conditions empirically can enhance the qualitative validation of substitutions in cases where direct validation data are lacking.

Journal of Animal Ecology↗
USGS2003

Isolation and characterization of novel waterfowl microsatellite loci: Cross-species comparisons and research applications

Waterfowl constitute an ecologically diverse group which are the subject of extensive research (e.g. see reviews in Batt et al . 1992), and are intensively managed (Nichols et al .1995). Genetic studies utilizing allozyme electrophoresis and mitochondrial (mt)DNA have provided valuable information on waterfowl ecology and evolutionary history (Cooke & Buckley 1987). However, highly variable molecular genetic markers (e.g. multilocus minisatellites; Triggs et al. 1992) have not generally been identified for this group.

Molecular Ecology↗
USGS2010

On the application of multilevel modeling in environmental and ecological studies

This paper illustrates the advantages of a multilevel/hierarchical approach for predictive modeling, including flexibility of model formulation, explicitly accounting for hierarchical structure in the data, and the ability to predict the outcome of new cases. As a generalization of the classical approach, the multilevel modeling approach explicitly models the hierarchical structure in the data by considering both the within- and between-group variances leading to a partial pooling of data across all levels in the hierarchy. The modeling framework provides means for incorporating variables at different spatiotemporal scales. The examples used in this paper illustrate the iterative process of model fitting and evaluation, a process that can lead to improved understanding of the system being studied.

Ecology↗
USGS2022

Animal tracing with sulfur isotopes: Spatial segregation and climate variability in Africa likely contribute to population trends of a migratory songbird

Climatic conditions affect animals but range-wide impacts at the population level remain largely unknown, especially in migratory species. However, studying climate–population relationships is still challenging in small migrants due to a lack of efficient and cost-effective geographic tracking method. Spatial distribution patterns of environmental stable isotopes (so called ‘isoscapes’) generally overcome these limitations but none of the currently available isoscapes provide a substantial longitudinal gradient in species-rich sub-Saharan Africa. In this region, sulphur ( δ 34 S) has not been sufficiently explored on a larger scale. We developed a δ 34 S isoscape to trace animal origins in sub-Saharan Africa by coupling known-origin samples from tracked migratory birds with continental remotely sensed environmental data building on environment– δ 34 S relationships using a flexible machine learning technique. Furthermore, we link population-specific nonbreeding grounds with interannual climatic variation that might translate to breeding population trends. The predicted δ 34 S isotopic map featured east–west and coast-to-inland isotopic gradients and was applied to predict nonbreeding grounds of three breeding populations of Eurasian Reed Warblers Acrocephalus scirpaceus with two distinct migratory phenotypes. Breeding populations as well as migratory phenotypes exhibited large-scale segregation within the African nonbreeding range. These regions also differed substantially in the interannual climatic variation, with higher interannual variability in the eastern part of the range during 2001–2012. Over the same period, the eastern European breeding population seemed to have experienced a more steep decline in population size. The link between migratory patterns and large-scale climatic variability appears important to better understand population trajectories in many declining migratory animals. We believe animal tracing using sulphur isotopes will facilitate these efforts and offers manifold ecological and forensic applications in the biodiversity hotspot of sub-Saharan Africa.

Journal of Animal Ecology↗
USGS2015

Empirical evaluation of the conceptual model underpinning a regional aquatic long-term monitoring program using causal modelling

Conceptual models are an integral facet of long-term monitoring programs. Proposed linkages between drivers, stressors, and ecological indicators are identified within the conceptual model of most mandated programs. We empirically evaluate a conceptual model developed for a regional aquatic and riparian monitoring program using causal models (i.e., Bayesian path analysis). We assess whether data gathered for regional status and trend estimation can also provide insights on why a stream may deviate from reference conditions. We target the hypothesized causal pathways for how anthropogenic drivers of road density, percent grazing, and percent forest within a catchment affect instream biological condition. We found instream temperature and fine sediments in arid sites and only fine sediments in mesic sites accounted for a significant portion of the maximum possible variation explainable in biological condition among managed sites. However, the biological significance of the direct effects of anthropogenic drivers on instream temperature and fine sediments were minimal or not detected. Consequently, there was weak to no biological support for causal pathways related to anthropogenic drivers’ impact on biological condition. With weak biological and statistical effect sizes, ignoring environmental contextual variables and covariates that explain natural heterogeneity would have resulted in no evidence of human impacts on biological integrity in some instances. For programs targeting the effects of anthropogenic activities, it is imperative to identify both land use practices and mechanisms that have led to degraded conditions (i.e., moving beyond simple status and trend estimation). Our empirical evaluation of the conceptual model underpinning the long-term monitoring program provided an opportunity for learning and, consequently, we discuss survey design elements that require modification to achieve question driven monitoring, a necessary step in the practice of adaptive monitoring. We suspect our situation is not unique and many programs may suffer from the same inferential disconnect. Commonly, the survey design is optimized for robust estimates of regional status and trend detection and not necessarily to provide statistical inferences on the causal mechanisms outlined in the conceptual model, even though these relationships are typically used to justify and promote the long-term monitoring of a chosen ecological indicator. Our application demonstrates a process for empirical evaluation of conceptual models and exemplifies the need for such interim assessments in order for programs to evolve and persist.

California, Colorado, Idaho, Montana, Nevada, Oreg↗
USGS2016

Estimating population density and connectivity of American mink using spatial capture-recapture

Estimating the abundance or density of populations is fundamental to the conservation and management of species, and as landscapes become more fragmented, maintaining landscape connectivity has become one of the most important challenges for biodiversity conservation. Yet these two issues have never been formally integrated together in a model that simultaneously models abundance while accounting for connectivity of a landscape. We demonstrate an application of using capture–recapture to develop a model of animal density using a least-cost path model for individual encounter probability that accounts for non-Euclidean connectivity in a highly structured network. We utilized scat detection dogs ( Canis lupus familiaris ) as a means of collecting non-invasive genetic samples of American mink ( Neovison vison ) individuals and used spatial capture–recapture models (SCR) to gain inferences about mink population density and connectivity. Density of mink was not constant across the landscape, but rather increased with increasing distance from city, town, or village centers, and mink activity was associated with water. The SCR model allowed us to estimate the density and spatial distribution of individuals across a 388 km 2 area. The model was used to investigate patterns of space usage and to evaluate covariate effects on encounter probabilities, including differences between sexes. This study provides an application of capture–recapture models based on ecological distance, allowing us to directly estimate landscape connectivity. This approach should be widely applicable to provide simultaneous direct estimates of density, space usage, and landscape connectivity for many species.

Ecological Applications↗
USGS2021

The spatial-temporal relationship of blue-winged teal to domestic poultry: Movement state modeling of a highly mobile avian influenza host

1. Migratory waterfowl facilitate long distance dispersal of zoonotic pathogens and are increasingly recognized as contributing to the geographic spread of avian influenza viruses (AIV). AIV are globally distributed and have the potential to produce highly contagious poultry disease, economically impact both large-scale and backyard poultry producers, and raise the specter of epidemics and pandemics in human populations. 2. Because migratory waterfowl behavior varies across multiple spatial and temporal scales, the timing and distribution of wild bird AIV introductions to poultry are also heterogeneous in time and space. To help reduce economic impacts to the poultry industry and enable poultry producers to better anticipate when and where poultry outbreaks may occur, it is critically important to consider the movement ecology of the waterfowl species transporting and transmitting AIV. 3. We used telemetry for a geographically widespread and common AIV host, blue-winged teal ( Spatula discors ; BWTE), to model reservoir host movement states with respect to backyard and commercial poultry facilities in the United States. Our modeling framework enabled us to estimate wild bird proximity to poultry facilities while concurrently assessing the influence of poultry facilities on BWTE movement state transition. Our primary objective was to estimate the likelihood of duck and poultry overlap by estimating when and where BWTE were geographically closest to poultry. 4. Synthesis and applications . Migratory waterfowl facilitate dispersal of the avian influenza viruses that cause highly contagious poultry disease. Movement analysis of blue-winged teal indicates that spatio-temporal overlap between wild birds and poultry facilities varies by season, the poultry type produced (e.g., turkey, chicken), and if the facility is a commercial or backyard operation. These findings are broadly applicable to disease ecology research and can be applied by poultry producers to improve bio-security, enhance poultry management, and prioritize disease surveillance efforts.

Journal of Applied Ecology↗
USGS2012

StreamStats in North Carolina: A water-resources Web application

A statewide StreamStats application for North Carolina was developed in cooperation with the North Carolina Department of Transportation following completion of a pilot application for the upper French Broad River basin in western North Carolina (Wagner and others, 2009). StreamStats for North Carolina, available at http://water.usgs.gov/osw/streamstats/north_carolina.html, is a Web-based Geographic Information System (GIS) application developed by the U.S. Geological Survey (USGS) in consultation with Environmental Systems Research Institute, Inc. (Esri) to provide access to an assortment of analytical tools that are useful for water-resources planning and management (Ries and others, 2008). The StreamStats application provides an accurate and consistent process that allows users to easily obtain streamflow statistics, basin characteristics, and descriptive information for USGS data-collection sites and user-selected ungaged sites. In the North Carolina application, users can compute 47 basin characteristics and peak-flow frequency statistics (Weaver and others, 2009; Robbins and Pope, 1996) for a delineated drainage basin. Selected streamflow statistics and basin characteristics for data-collection sites have been compiled from published reports and also are immediately accessible by querying individual sites from the web interface. Examples of basin characteristics that can be computed in StreamStats include drainage area, stream slope, mean annual precipitation, and percentage of forested area (Ries and others, 2008). Examples of streamflow statistics that were previously available only through published documents include peak-flow frequency, flow-duration, and precipitation data. These data are valuable for making decisions related to bridge design, floodplain delineation, water-supply permitting, and sustainable stream quality and ecology. The StreamStats application also allows users to identify stream reaches upstream and downstream from user-selected sites and obtain information for locations along streams where activities occur that may affect streamflow conditions. This functionality can be accessed through a map-based interface with the user’s Web browser, or individual functions can be requested remotely through Web services (Ries and others, 2008).

North Carolina↗
USGS2010

Detecting temporal trends in species assemblages with bootstrapping procedures and hierarchical models

Quantifying patterns of temporal trends in species assemblages is an important analytical challenge in community ecology. We describe methods of analysis that can be applied to a matrix of counts of individuals that is organized by species (rows) and time-ordered sampling periods (columns). We first developed a bootstrapping procedure to test the null hypothesis of random sampling from a stationary species abundance distribution with temporally varying sampling probabilities. This procedure can be modified to account for undetected species. We next developed a hierarchical model to estimate species-specific trends in abundance while accounting for species-specific probabilities of detection. We analysed two long-term datasets on stream fishes and grassland insects to demonstrate these methods. For both assemblages, the bootstrap test indicated that temporal trends in abundance were more heterogeneous than expected under the null model. We used the hierarchical model to estimate trends in abundance and identified sets of species in each assemblage that were steadily increasing, decreasing or remaining constant in abundance over more than a decade of standardized annual surveys. Our methods of analysis are broadly applicable to other ecological datasets, and they represent an advance over most existing procedures, which do not incorporate effects of incomplete sampling and imperfect detection.

Philosophical Transactions of the Royal Society B:↗
USGS2019

The area under the precision‐recall curve as a performance metric for rare binary events

Species distribution models are used to study biogeographic patterns and guide decision‐making. The variable quality of these models makes it critical to assess whether a model's outputs are suitable for the intended use, but commonly used evaluation approaches are inappropriate for many ecological contexts. In particular, unrealistically high performance assessments have been associated with models for rare species and predictions over large geographic extents. We evaluated the area under the precision‐recall curve (AUC‐PR) as a performance metric for rare binary events, focusing on the assessment of species distribution models. Precision is the probability that a species is present given a predicted presence, while recall (more commonly called sensitivity) is the probability the model predicts presence in locations where the species has been observed. We simulated species at three levels of prevalence, compared AUC‐PR and the area under the receiver operating characteristic curve (AUC‐ROC) when the geographic extent of predictions was increased and assessed how well each metric reflected a model's utility to guide surveys for new populations. AUC‐PR was robust to species rarity and, unlike AUC‐ROC, not affected by an increasing geographic extent. The major advantages of AUC‐PR arise because it does not incorporate correctly predicted absences and is therefore less prone to exaggerate model performance for unbalanced datasets. AUC‐PR and precision were useful indicators of a model's utility for guiding surveys. We show that AUC‐PR has important advantages for evaluating models of rare species, and its benefits in the context of unbalanced binary responses will make it applicable for other ecological studies. By not considering the true negative quadrant of the confusion matrix, AUC‐PR ameliorates issues that arise when the geographic extent is increased beyond the species’ range or when a large number of background points are used when absence information is unavailable. However, no single metric captures all aspects of performance nor provides an absolute index that can be compared across datasets. Our results indicate AUC‐PR and precision can provide useful and intuitive metrics for evaluating a model's utility for guiding sampling, and can complement other metrics to help delineate a model's appropriate use.

Methods in Ecology and Evolution↗
USGS2015

Management applications of discontinuity theory

Human impacts on the environment are multifaceted and can occur across distinct spatiotemporal scales. Ecological responses to environmental change are therefore difficult to predict, and entail large degrees of uncertainty. Such uncertainty requires robust tools for management to sustain ecosystem goods and services and maintain resilient ecosystems. We propose an approach based on discontinuity theory that accounts for patterns and processes at distinct spatial and temporal scales, an inherent property of ecological systems. Discontinuity theory has not been applied in natural resource management and could therefore improve ecosystem management because it explicitly accounts for ecological complexity. Synthesis and applications . We highlight the application of discontinuity approaches for meeting management goals. Specifically, discontinuity approaches have significant potential to measure and thus understand the resilience of ecosystems, to objectively identify critical scales of space and time in ecological systems at which human impact might be most severe, to provide warning indicators of regime change, to help predict and understand biological invasions and extinctions and to focus monitoring efforts. Discontinuity theory can complement current approaches, providing a broader paradigm for ecological management and conservation.

Journal of Applied Ecology↗
USGS2005

Landscape characteristics of Rhizophora mangle forests and propagule deposition in coastal environments of Florida (USA)

Field dispersal studies are seldom conducted at regional scales even though reliable information on mid-range dispersal distance is essential for models of colonization. The purpose of this study was to examine the potential distance of dispersal of Rhizophora mangle propagules by comparing deposition density with landscape characteristics of mangrove forests. Propagule density was estimated at various distances to mangrove sources (R. mangle) on beaches in southwestern Florida in both high-and low-energy environments, either facing open gulf waters vs. sheltered, respectively. Remote sensing and Geographic Information Systems were used to identify source forests and to determine their landscape characteristics (forest size and distance to deposition area) for the regression analyses. Our results indicated that increasing density of propagules stranded on beaches was related negatively to the distance of the deposition sites from the nearest stands of R. mangle and that deposition was greatly diminished 2 km or more from the source. Measures of fragmentation such as the area of the R. mangle forests were related to propagule deposition but only in low-energy environments. Our results suggest that geographic models involving the colonization of coastal mangrove systems should include dispersal dynamics at mid-range scales, i.e., for our purposes here, beyond the local scale of the forest and up to 5 km distant. Studies of mangrove propagule deposition at various spatial scales are key to understanding regeneration limitations in natural gaps and restoration areas. Therefore, our study of mid-range propagule dispersal has broad application to plant ecology, restoration, and modeling. ?? Springer 2005.

Landscape Ecology↗
USGS2014

Estimating landscape resistance to dispersal

Dispersal is an inherently spatial process that can be affected by habitat conditions in sites encountered by dispersers. Understanding landscape resistance to dispersal is important in connectivity studies and reserve design, but most existing methods use resistance functions with cost parameters that are subjectively chosen by the investigator. We develop an analytic approach allowing for direct estimation of resistance parameters that folds least cost path methods typically used in simulation approaches into a formal statistical model of dispersal distributions. The core of our model is a frequency distribution of dispersal distances expressed as least cost distance rather than Euclidean distance, and which includes terms for feature-specific costs to dispersal and sex (or other traits) of the disperser. The model requires only origin and settlement locations for multiple individuals, such as might be obtained from mark–recapture studies or parentage analyses, and maps of the relevant habitat features. To evaluate whether the model can estimate parameters correctly, we fit our model to data from simulated dispersers in three kinds of landscapes (in which resistance of environmental variables was categorical, continuous with a patchy configuration, or continuous in a trend pattern). We found maximum likelihood estimators of resistance and individual trait parameters to be approximately unbiased with moderate sample sizes. We applied the model to a small grizzly bear dataset to demonstrate how this approach could be used when the primary interest is in the prediction of costs and found that estimates were consistent with expectations based on bear ecology. Our method has important practical applications for testing hypotheses about dispersal ecology and can be used to inform connectivity planning efforts, via the resistance estimates and confidence intervals, which can be used to create a data-driven resistance surface.

Landscape Ecology↗
USGS2006

The future of imaging spectroscopy - Prospective technologies and applications

Spectroscopy has existed for more than three centuries now. Nonetheless, significant scientific advances have been achieved. We discuss the history of spectroscopy in relation to emerging technologies and applications. Advanced focal plane arrays, optical design, and intelligent on-board logic are prime prospective technologies. Scalable approaches in pre-processing of imaging spectrometer data will receive additional focus. Finally, we focus on new applications monitoring transitional ecological zones, where human impact and disturbance have highest impact as well as in monitoring changes in our natural resources and environment We conclude that imaging spectroscopy enables mapping of biophysical and biochemical variables of the Earth's surface and atmospheric composition with unprecedented accuracy.

Conference Paper↗
USGS2022

Priorities for translating goodwill between movement ecologists and conservation practitioners into effective collaboration

Addressing ongoing biodiversity loss requires collaboration between conservation scientists and practitioners. However, such collaboration has proved challenging. Despite the potential importance of tracking animal movements for conservation, reviews of the tracking literature have identified a gap between the academic discipline of movement ecology and its application to biodiversity conservation. Through structured conversations with movement ecologists and conservation practitioners, we aimed to understand whether the identified gap is also perceived in practice, and if so, what factors hamper collaboration and how these factors can be remediated. We found that both groups are motivated and willing to collaborate. However, because their motivations differ, there is potential for misunderstandings and miscommunications. In addition, external factors such as funder requirements, academic metrics, and journal scopes may limit the applicability of scientific results in a conservation setting. Potential solutions we identified included improved communication and better presentation of results, acknowledging each other's motivations and desired outputs, and adjustment of funder priorities. Addressing gaps between science and implementation can enhance collaboration and support conservation action to address the global biodiversity crisis more effectively.

Conservation Science and Practice↗
USGS2004

Comparison of fluorescence microscopy and solid-phase cytometry methods for counting bacteria in water

Total direct counts of bacterial abundance are central in assessing the biomass and bacteriological quality of water in ecological and industrial applications. Several factors have been identified that contribute to the variability in bacterial abundance counts when using fluorescent microscopy, the most significant of which is retaining an adequate number of cells per filter to ensure an acceptable level of statistical confidence in the resulting data. Previous studies that have assessed the components of total-direct-count methods that contribute to this variance have attempted to maintain a bacterial cell abundance value per filter of approximately 10 6 cells filter -1 . In this study we have established the lower limit for the number of bacterial cells per filter at which the statistical reliability of the abundance estimate is no longer acceptable. Our results indicate that when the numbers of bacterial cells per filter were progressively reduced below 10 5 , the microscopic methods increasingly overestimated the true bacterial abundance (range, 15.0 to 99.3%). The solid-phase cytometer only slightly overestimated the true bacterial abundances and was more consistent over the same range of bacterial abundances per filter (range, 8.9 to 12.5%). The solid-phase cytometer method for conducting total direct counts of bacteria was less biased and performed significantly better than any of the microscope methods. It was also found that microscopic count data from counting 5 fields on three separate filters were statistically equivalent to data from counting 20 fields on a single filter.

Applied and Environmental Microbiology↗
USGS1958

Periodic heat flow in a stratified medium with application to permafrost problems

Solutions to the Fourier heat equation for quasi-steady periodic flow in a stratified semi-infinite medium can be obtained readily by standard methods. The results have wide application to studies of earth-temperature variations induced by diurnal, annual, and other periodic variations in ground surface temperature. Much of the previous work on this subject has been interpreted with reference to the solution for the homogeneous case; and this can be seriously in error when applied to stratified earth materials. One application of the theory is to the important problem of determining the minimum thickness of gravel fill required to maintain the material on which it rests (the subgrade) in a perennially frozen state in permafrost areas. The results indicate that the required fill thickness is quite sensitive to the thermal properties of the subgrade. If a thin layer of material with low thermal contact coefficient, such as spruce logs, is placed between the fill and subgrade, the thickness of fill required to maintain undisturbed permafrost can be greatly reduced. The thermal properties of the soil beneath the layer supporting plant growth can exercise an important influence on the temperature in that layer. This effect, which cannot be explained by studies of the ground surface and the surficial layer, is likely to have important application to plant ecology in the Arctic.

Open-File Report↗
USGS2025

A low-cost approach to monitoring streamflow dynamics in small, headwater streams using timelapse imagery and a deep learning model

Despite their ubiquity and importance as freshwater habitat, small headwater streams are under monitored by existing stream gage networks. To address this gap, we describe a low-cost, non-contact, and low-effort method that enables organizations to monitor streamflow dynamics in small headwater streams. The method uses a camera to capture repeat images of the stream from a fixed position. A person then annotates pairs of images, in each case indicating which image has more apparent streamflow or indicating equal flow if no difference is discernible. A deep learning modelling framework called Streamflow Rank Estimation (SRE) is then trained on the annotated image pairs and applied to rank all images from highest to lowest apparent streamflow. From this result a relative hydrograph can be derived. We found that our modelled relative hydrograph dynamics matched the observed hydrograph dynamics well for 11 cameras at 8 streamflow sites in western Massachusetts. Higher performance was observed during the annotation period (median Kendall’s Tau rank correlation 0.75 with range 0.6–0.83) than after it (median Kendall’s Tau 0.59 with range 0.34 – 0.74). We found that annotation performance was generally consistent across the eleven camera sites and two individual annotators and was positively correlated with streamflow variability at a site. A scaling simulation determined that model performance improvements were limited after 1,000 annotation pairs. Our model’s estimates of relative flow, while not equivalent to absolute flow, may still be useful for many applications, such as ecological modelling and calculating event-based hydrological statistics (e.g., the number of out-of-bank floods). We anticipate this method will be a valuable tool to extend existing stream monitoring networks and provide new insights on dynamic headwater systems.

EGUSphere↗