SEARCH · Geology Reports

Results for “Ecological Modeling”

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 1,801 records · Page 100Linked to original sources

USGS2016

Prey partitioning and use of insects by juvenile sockeye salmon and a potential competitor, threespine stickleback, in Afognak Lake, Alaska

Freshwater growth of juvenile sockeye salmon ( Oncorhynchus nerka ) depends upon the quality and quantity of prey and interactions with potential competitors in the foraging environment. To a large extent, knowledge about the ecology of lake-rearing juvenile sockeye salmon has emerged from studies of commercially important runs returning to deep nursery lakes, yet information from shallow nursery lakes (mean depth ≤ 10 m) is limited. We examined seasonal and ontogenetic variation in diets of juvenile sockeye salmon ( N = 219, 30–85 mm) and an abundant potential competitor, threespine stickleback ( Gasterosteus aculeatus ; N = 198, 42–67 mm), to understand their foraging ecology and potential trophic interactions in a shallow Alaska lake. This study revealed that adult insects made up 74% of all sockeye salmon diets by weight and were present in 98% of all stomachs in Afognak Lake during the summer of 2013. Diets varied temporally for all fishes, but small sockeye salmon (<60 mm) showed a distinct shift in consumption from zooplankton in early summer to adult insects in late summer. We found significant differences in diet composition between sockeye salmon and threespine stickleback and the origin of their prey indicated that they also separated their use of habitat on a fine scale; however, the two species showed overlap in size selectivity of zooplankton prey. Considering that aquatic insects can be a primary resource for juvenile sockeye salmon in Afognak Lake, we encourage the development of nursery lake carrying capacity models that include aquatic insects as a prey source for sockeye salmon.

Alaska↗

USGS2018

Sympatry or syntopy? Investigating drivers of distribution and co‐occurrence for two imperiled sea turtle species in Gulf of Mexico neritic waters

Animals co‐occurring in a region (sympatry) may use the same habitat (syntopy) within that region. A central aim in ecology is determining what factors drive species distributions (i.e., abiotic conditions, dispersal limitations, and/or biotic interactions). Assessing the degree of biotic interactions can be difficult for species with wide ranges at sea. This study investigated the spatial ecology of two sea turtle species that forage on benthic invertebrates in neritic GoM waters: Kemp's ridleys ( Lepidochelys kempii ) and loggerheads ( Caretta caretta ). We used satellite tracking and modeled behavioral modes, then calculated individual home ranges, compared foraging areas, and determined extent of co‐occurrence. Using six environmental variables and principal component analysis, we assessed similarity of chosen foraging sites. We predicted foraging location (eco‐region) based on species, nesting site, and turtle size. For 127 turtles (64 Kemp's ridleys, 63 loggerheads) tracked from 1989 to 2013, foraging home ranges were nine to ten times larger for Kemp's ridleys than for loggerheads. Species intersected off all U.S. coasts and the Yucatán Peninsula, but co‐occurrence areas were small compared to species' distributions. Kemp's ridley foraging home ranges were concentrated in the northern GoM, whereas those for loggerheads were concentrated in the eastern GoM. The two species were different in all habitat variables compared (latitude, longitude, distance to shore, net primary production, mean sea surface temperature, and bathymetry). Nesting site was the single dominant variable that dictated foraging ecoregion. Although Kemp's ridleys and loggerheads may compete for resources, the separation in foraging areas, significant differences in environmental conditions, and importance of nesting location on ecoregion selection (i.e., dispersal ability) indicate that adult females of these species do not interact greatly during foraging and that dispersal and environmental factors more strongly determine their distributions. These species show sympatry in this region but evidence for syntopy was rare.

Ecology and Evolution↗

USGS2010

Constructing an interdisciplinary flow regime recommendation

It is generally agreed that river rehabilitation most often relies on restoring a more natural flow regime, but credibly defining the desired regime can be problematic. I combined four distinct methods to develop and refine month-by-month and event-based flow recommendations to protect and partially restore the ecological integrity of the Cache la Poudre River through Fort Collins, Colorado. A statistical hydrologic approach was used to summarize the river's natural flow regime and set provisional monthly flow targets at levels that were historically exceeded 75% of the time. These preliminary monthly targets were supplemented using results from three Poudre-specific disciplinary studies. A substrate maintenance flow model was used to better define the high flows needed to flush accumulated sediment from the river's channel and help sustain the riparian zone in this snowmelt-dominated river. A hydraulic/habitat model and a water temperature model were both used to better define the minimum flows necessary to maintain a thriving cool water fishery. The result is a range of recommended monthly flows and daily flow guidance illustrating the advantage of combining a wide range of available disciplinary information, supplemented by judgment based on ecological principles and a general understanding of river ecosystems, in a highly altered, working river. ?? 2010 American Water Resources Association.

Journal of the American Water Resources Associatio↗

USGS2014

Guidelines for a priori grouping of species in hierarchical community models

Recent methodological advances permit the estimation of species richness and occurrences for rare species by linking species-level occurrence models at the community level. The value of such methods is underscored by the ability to examine the influence of landscape heterogeneity on species assemblages at large spatial scales. A salient advantage of community-level approaches is that parameter estimates for data-poor species are more precise as the estimation process borrows from data-rich species. However, this analytical benefit raises a question about the degree to which inferences are dependent on the implicit assumption of relatedness among species. Here, we assess the sensitivity of community/group-level metrics, and individual-level species inferences given various classification schemes for grouping species assemblages using multispecies occurrence models. We explore the implications of these groupings on parameter estimates for avian communities in two ecosystems: tropical forests in Puerto Rico and temperate forests in northeastern United States. We report on the classification performance and extent of variability in occurrence probabilities and species richness estimates that can be observed depending on the classification scheme used. We found estimates of species richness to be most precise and to have the best predictive performance when all of the data were grouped at a single community level. Community/group-level parameters appear to be heavily influenced by the grouping criteria, but were not driven strictly by total number of detections for species. We found different grouping schemes can provide an opportunity to identify unique assemblage responses that would not have been found if all of the species were analyzed together. We suggest three guidelines: (1) classification schemes should be determined based on study objectives; (2) model selection should be used to quantitatively compare different classification approaches; and (3) sensitivity of results to different classification approaches should be assessed. These guidelines should help researchers apply hierarchical community models in the most effective manner.

Ecology and Evolution↗

USGS2019

Modern pollen-assemblages data from small lakes paired with local forest-composition data in northeastern United States

For the past century, pollen analysis has served as a primary tool for inferring past changes in vegetation composition and structure (Birks et al. 2016, Edwards et al. 2017). Pollen-based inferences are supported by empirical studies comparing modern pollen assemblages with modern vegetation composition. In one approach, pollen abundances (usually percentages) for individual taxa are compared directly with quantitative estimates of abundance in surrounding vegetation (Jackson 1994, Davis 2000). This approach has been applied most frequently using spatially extensive but coarse-scale forest inventory data (Webb et al. 1981, Bradshaw and Webb 1985, Prentice & Webb 1986, Prentice et al. 1987, Paciorek & McLachlan 2009, Dawson et al. 2016, Kujawa et al. 2016). In these studies, forest composition cannot usually be estimated accurately within a 1- to 10 km radius of the individual sites owing to limited spatial density of forest inventory data. A few studies have compared vegetation composition within 50-100 m of pollen-sampling sites, but in these cases the pollen is from forest-floor assemblages (Bradshaw 1981, Jackson & Wong 1994, Jackson & Kearsley 1998) or from small forest hollows (Calcote 1995, 1998, Parshall & Calcote 2001). Largely lacking are pollen assemblage data from lake sediments paired with local forest composition, measured within 100 to 1000 m of the lake margins (Jackson 1990). This absence represents a substantial gap in ability to understand and model pollen-vegetation relationships, because lakes are the primary source of fossil-pollen sequences worldwide, and because the leptokurtic nature of pollen dispersal ensures that local vegetation has an important effect on pollen composition in sediments (Jackson 1994, Sugita 1994, 2007a, 2007b, Jackson & Lyford 1999). Here, I present a data set pairing modern pollen assemblages from 33 small lakes in the forested northeastern United States (Fig. 1) with forest composition data measured within 20, 50, 100, 500, and 1000 metres of the lake margins. This data set incorporates most of the sites used in Jackson (1990), adding 16 new sites and delivering the vegetation data by species in absolute units (i.e., total basal area), which allows various weightings and transformations to be applied. The data set should be of value to paleoecologists and forest ecologists in understanding, modeling, and validating the pollen-vegetation relationships that are at the heart of paleoecological inference.

Northeastern United States↗

USGS2014

Applying threshold concepts to conservation management of dryland ecosystems: Case studies on the Colorado Plateau

Ecosystems may occupy functionally distinct alternative states, some of which are more or less desirable from a management standpoint. Transitions from state to state are usually associated with a particular trigger or sequence of triggers, such as the addition or subtraction of a disturbance. Transitions are often not linear, rather it is common to see an abrupt transition come about even though the trigger increases only incrementally; these are examples of threshold behaviors. An ideal monitoring program, such as the National Park Service’s Inventory and Monitoring Program, would quantify triggers, and be able to inform managers when measurements of a trigger are approaching a threshold so that management action can avoid an unwanted state transition. Unfortunately, both triggers and the threshold points at which state transitions occur are generally only partially known. Using case studies, we advance a general procedure to help identify triggers and estimate where threshold dynamics may occur. Our procedure is as follows: (1) Operationally define the ecosystem type being considered; we suggest that the ecological site concept of the Natural Resource Conservation Service is a useful system, (2) Using all available a priori knowledge to develop a state-and-transition model (STM), which defines possible ecosystem states, plausible transitions among them and likely triggers, (3) Validate the STM by verifying the existence of its states to the greatest degree possible, (4) Use the STM model to identify transitions and triggers likely to be detectable by a monitoring program, and estimate to the greatest degree possible the value of a measurable indicator of a trigger at the point that a state transition is imminent (tipping point), and values that may indicate when management intervention should be considered (assessment points). We illustrate two different methods for attaining these goals using a data-rich case study in Canyonlands National Park, and a data-poor case study in Wupatki National Monument. In the data-rich case, STMs are validated and revised, and tipping and assessment points are estimated using statistical analysis of data. In the data-poor case, we develop an iterative expert opinion survey approach to validate the degree of confidence in an STM, revise the model, identify lack of confidence in specific model components, and create reasonable first approximations of tipping and assessment points, which can later be refined when more data are available. Our goal should be to develop the best set of models possible given the level of information available to support decisions, which is often not much. The approach presented here offers a flexible means of achieving this goal, and determining specific research areas in need of study.

Book chapter↗

USGS2014

Insights into biodegradation through depth-resolved microbial community functional and structural profiling of a crude-oil contaminant plume

Small-scale geochemical gradients are a key feature of aquifer contaminant plumes, highlighting the need for functional and structural profiling of corresponding microbial communities on a similar scale. The purpose of this study was to characterize the microbial functional and structural diversity with depth across representative redox zones of a hydrocarbon plume and an adjacent wetland, at the Bemidji Oil Spill site. A combination of quantitative PCR, denaturing gradient gel electrophoresis, and pyrosequencing were applied to vertically sampled sediment cores. Levels of the methanogenic marker gene, methyl coenzyme-M reductase A (mcrA), increased with depth near the oil body center, but were variable with depth further downgradient. Benzoate degradation N (bzdN) hydrocarbon-degradation gene, common to facultatively anaerobic Azoarcus spp., was found at all locations, but was highest near the oil body center. Microbial community structural differences were observed across sediment cores, and bacterial classes containing known hydrocarbon degraders were found to be low in relative abundance. Depth-resolved functional and structural profiling revealed the strongest gradients in the iron-reducing zone, displaying the greatest variability with depth. This study provides important insight into biogeochemical characteristics in different regions of contaminant plumes, which will aid in improving models of contaminant fate and natural attenuation rates.

Minnesota↗

USGS2018

Downscaling future climate change projections over Puerto Rico using a non-hydrostatic atmospheric model

We present results from 20-year “high-resolution” regional climate model simulations of precipitation change for the sub-tropical island of Puerto Rico. The Japanese Meteorological Agency Non-Hydrostatic Model (NHM) operating at a 2-km grid resolution is nested inside the Regional Spectral Model (RSM) at 10-km grid resolution, which in turn is forced at the lateral boundaries by the Community Climate System Model (CCSM4). At this resolution, the climate change experiment allows for deep convection in model integrations, which is an important consideration for sub-tropical regions in general, and on islands with steep precipitation gradients in particular that strongly influence local ecological processes and the provision of ecosystem services. Projected precipitation change for this region of the Caribbean is simulated for the mid-twenty-first century (2041–2060) under the RCP8.5 climate-forcing scenario relative to the late twentieth century (1986–2005). The results show that by the mid-twenty-first century, there is an overall rainfall reduction over the island for all seasons compared to the recent climate but with diminished mid-summer drought (MSD) in the northwestern parts of the island. Importantly, extreme rainfall events on sub-daily and daily time scales also become slightly less frequent in the projected mid-twenty-first-century climate over most regions of the island.

Puerto Rico↗

USGS2019

Marshes are the new beaches: Integrating sediment transport into restoration planning

Recent coastal storms and associated recovery efforts have led to increased investment in nature-based coastal protection, including restoration of salt marshes and construction of living shorelines. In particular, many of these efforts focus on increasing vertical elevation through sediment nourishment, where sediment is removed from the tidal channel and placed on the marsh plain, or preventing lateral erosion through shoreline protection. In the USA alone, millions of dollars have been allocated or spent on these coastal protection solutions over the last few decades because of their perceived sustainability and ecologically positive co-benefits including habitat provision and carbon sequestration. These projects would benefit from integration of sediment transport pathways, budgets, and metrics during planning and modeling of restoration outcomes, in order to evaluate sustainability before investment. This is analogous to the decades of experience with coastal management and engineering on the open coast. Salt marshes are geomorphic features that rely partially on external sediment supply to maintain their network of tidal channels, intertidal flats, and marsh plain. Removing sediment from one component of the overall system to nourish another component may be counterproductive, given that the net sediment budget is unchanged. For example, dredging a tidal channel beyond its equilibrium condition will cause it to fill with sediment from the tidal flat or elsewhere in the system. This may cause slumping of the marsh edge, or over-deepening of other sections of the channel to compensate. Similarly, shoreline protection that prevents edge erosion hampers the marsh plain’s ability to accrete on the levee and naturally transgress landward or it starves other components of the system of regularly supplied sediment. A limited vertical or lateral-only perspective, instead of a three-dimensional perspective, during project planning and evaluation may lead to suboptimal decision-making regarding restoration priorities, approaches, and outcomes. I contend that before significant investments are made in marsh restoration through sediment nourishment or shoreline protection, sediment transport measurements and models that consider sediment dynamics should be integrated into the early phases of restoration planning. This will help identify where and under what conditions marsh restoration will most likely be successful and economically justified. Triaging and prioritizing is then possible, which is a sustainable approach for restoration, given the persistent vulnerability of marshes to sea-level rise, storms, and sediment deficits.

Estuaries and Coasts↗

USGS2017

A floodplain continuum for Atlantic coast rivers of the Southeastern US: Predictable changes in floodplain biota along a river's length

Floodplains are among the world’s economically-most-valuable, environmentally-most-threatened, and yet conceptually-least-understood ecosystems. Drawing on concepts from existing riverine and wetland models, and empirical data from floodplains of Atlantic Coast rivers in the Southeastern US (and elsewhere when possible), we introduce a conceptual model to explain a continuum of longitudinal variation in floodplain ecosystem functions with a particular focus on biotic change. Our hypothesis maintains that major controls on floodplain ecology are either external (ecotonal interactions with uplands or stream/river channels) or internal (wetland-specific functions), and the relative importance of these controls changes progressively from headwater to mid-river to lower-river floodplains. Inputs of water, sediments, nutrients, flora, and fauna from uplands-to-floodplains decrease, while the impacts of wetland biogeochemistry and obligate wetland plants and animals within-floodplains increase, along the length of a river floodplain. Inputs of water, sediment, nutrients, and fauna from river/stream channels to floodplains are greatest mid-river, and lower either up- or down-stream. While the floodplain continuum we develop is regional in scope, we review how aspects may apply more broadly. Management of coupled floodplain-river ecosystems would be improved by accounting for how factors controlling the floodplain ecosystem progressively change along longitudinal riverine gradients.

Wetlands↗

USGS2017

Estimating linear temporal trends from aggregated environmental monitoring data

Trend estimates are often used as part of environmental monitoring programs. These trends inform managers (e.g., are desired species increasing or undesired species decreasing?). Data collected from environmental monitoring programs is often aggregated (i.e., averaged), which confounds sampling and process variation. State-space models allow sampling variation and process variations to be separated. We used simulated time-series to compare linear trend estimations from three state-space models, a simple linear regression model, and an auto-regressive model. We also compared the performance of these five models to estimate trends from a long term monitoring program. We specifically estimated trends for two species of fish and four species of aquatic vegetation from the Upper Mississippi River system. We found that the simple linear regression had the best performance of all the given models because it was best able to recover parameters and had consistent numerical convergence. Conversely, the simple linear regression did the worst job estimating populations in a given year. The state-space models did not estimate trends well, but estimated population sizes best when the models converged. We found that a simple linear regression performed better than more complex autoregression and state-space models when used to analyze aggregated environmental monitoring data.

Ecological Indicators↗

USGS2016

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Nature Climate Change↗

USGS2025

Tailwater residency patterns of Silver Carp at Kentucky Lock and Dam

Objective The management of invasive Silver Carp Hypophthalmichthys molitrix in the Tennessee River basin focuses on removal, and there is interest in extending removal efforts to the tailwater environments of high-head locks and dams along the Tennessee River, such as Kentucky Dam. We used acoustic telemetry data from Silver Carp to understand important ecological associations underlying their residence in the Kentucky Dam tailwater, measured by daily fish counts and mean residence time. Methods We used time-series-informed regression models, variance partitioning, and cross-correlation function analysis to associate six predictors, including lock and dam operations (total, spill gate, and turbine discharge and number of lockages), hydrology (tailwater elevation), and water temperature, with two measures of Silver Carp residency (daily counts and mean residence time). Results We found that spill-induced hydrology (total discharge + spill discharge + tailwater elevation) was negatively associated with daily counts but not with residence time, whereas temperature was positively associated with counts and negatively associated with residence times. Variance partitioning indicated that nearly all the variance in counts and residence times was jointly explained by temporal effects, lock and dam operations (discharge, tailwater elevation, and lockages), and temperature. The cross-correlations indicated that the counts were lagged by all predictors, sometimes up to 5 d, whereas residence times were lagged by both total and spill discharge and number of lockages. Conclusions We found that discharge and water temperature were principally associated with residency of Silver Carp in the Kentucky Dam tailwater. However, these associations were entirely temporally constrained, which can affect how strongly and how quickly Silver Carp respond to changing environmental conditions across different time scales. Managers can leverage these associations to plan removal periods where daily tailwater conditions/dam operations are favorable to invasive carp residence (e.g., >10°C and <2,500 m 3 /s) and adjust fishing effort to optimize removal rates in response to changing conditions.

Kentucky Lock and Dam↗

USGS2016

Nest survival is influenced by parental behaviour and heterospecifics in a mixed-species colony

Studies of avian nest success often focus on examining influences of variation in environmental and seasonal factors. However, in-depth evaluations can also incorporate variation in individual incubation behaviour to further advance our understanding of avian reproductive ecology. We examined these relationships in colonially nesting Black-crowned Night-Herons Nycticorax nycticorax using intensive video-monitoring methods to quantify incubation behaviours. We modelled nest survival as a function of both extrinsic factors and incubation behaviours over a 3-year period (2010–12) on Alcatraz Island, USA. Model-averaged parameter estimates indicated that nest survival increased as a function of greater incubation constancy (% of time spent incubating eggs within a 24-h period), and average daily precipitation throughout the nesting stage. Common Ravens Corvus corax are the only known nest predator of Night-Herons on Alcatraz Island, as on many other coastal Pacific islands. We also investigated the effects of heterospecific nesting of California Gulls Larus californicus and Western Gulls Larus occidentalis in a mixed-species colony with Night-Herons, based on nesting proximity data collected over a 2-year period (2011–12). This second analysis indicated that, in addition to incubation behaviours, nesting heterospecifics are an important factor for explaining variation in Night-Heron nest survival. However, contrary to our original expectation, we found that Night-Herons experienced increased nest survival with increasing distance from gull colony boundaries. These results may apply to other areas with multiple colonial nesting species and similar predator communities and climatic patterns.

Ibis↗

USGS2009

The changing global carbon cycle: Linking plant-soil carbon dynamics to global consequences

Most current climate-carbon cycle models that include the terrestrial carbon (C) cycle are based on a model developed 40 years ago by Woodwell & Whittaker (1968) and omit advances in biogeochemical understanding since that time. Their model treats net C emissions from ecosystems as the balance between net primary production (NPP) and heterotrophic respiration (HR, i.e. primarily decomposition). Under conditions near steady state, geographic patterns of decomposition closely match those of NPP, and net C emissions are adequately described as a simple balance of NPP and HR (the Woodwell-Whittaker model). This close coupling between NPP and HR occurs largely because of tight coupling between C and N (nitrogen) cycles and because NPP constrains the food available to heterotrophs. Processes in addition to NPP and HR become important to understanding net C emissions from ecosystems under conditions of rapid changes in climate, hydrology, atmospheric CO 2 , land cover, species composition and/or N deposition. Inclusion of these processes in climate-C cycle models would improve their capacity to simulate recent and future climatic change. Processes that appear critical to soil C dynamics but warrant further research before incorporation into ecosystem models include below-ground C flux and its partitioning among roots, mycorrhizas and exudates; microbial community effects on C sequestration; and the effects of temperature and labile C on decomposition. The controls over and consequences of these processes are still unclear at the ecosystem scale. Carbon fluxes in addition to NPP and HR exert strong influences over the climate system under conditions of rapid change. These fluxes include methane release, wildfire, and lateral transfers of food and fibre among ecosystems. Water and energy exchanges are important complements to C cycle feedbacks to the climate system, particularly under non-steady-state conditions. An integrated understanding of multiple ecosystem-climate feedbacks provides a strong foundation for policies to mitigate climate change. Synthesis . Current climate systems models that include only NPP and HR are inadequate under conditions of rapid change. Many of the recent advances in biogeochemical understanding are sufficiently mature to substantially improve representation of ecosystem C dynamics in these models.

Journal of Ecology↗

USGS2011

Inference about density and temporary emigration in unmarked populations

Few species are distributed uniformly in space, and populations of mobile organisms are rarely closed with respect to movement, yet many models of density rely upon these assumptions. We present a hierarchical model allowing inference about the density of unmarked populations subject to temporary emigration and imperfect detection. The model can be fit to data collected using a variety of standard survey methods such as repeated point counts in which removal sampling, double‐observer sampling, or distance sampling is used during each count. Simulation studies demonstrated that parameter estimators are unbiased when temporary emigration is either “completely random” or is determined by the size and location of home ranges relative to survey points. We also applied the model to repeated removal sampling data collected on Chestnut‐sided Warblers ( Dendroica pensylvancia ) in the White Mountain National Forest, USA. The density estimate from our model, 1.09 birds/ha, was similar to an estimate of 1.11 birds/ha produced by an intensive spot‐mapping effort. Our model is also applicable when processes other than temporary emigration affect the probability of being available for detection, such as in studies using cue counts. Functions to implement the model have been added to the R package unmarked .

New Hampshire↗

USGS2012

Evaluating the predictive abilities of community occupancy models using AUC while accounting for imperfect detection

The ability to accurately predict patterns of species' occurrences is fundamental to the successful management of animal communities. To determine optimal management strategies, it is essential to understand species-habitat relationships and how species habitat use is related to natural or human-induced environmental changes. Using five years of monitoring data in the Chesapeake and Ohio Canal National Historical Park, Maryland, USA, we developed four multi-species hierarchical models for estimating amphibian wetland use that account for imperfect detection during sampling. The models were designed to determine which factors (wetland habitat characteristics, annual trend effects, spring/summer precipitation, and previous wetland occupancy) were most important for predicting future habitat use. We used the models to make predictions of species occurrences in sampled and unsampled wetlands and evaluated model projections using additional data. Using a Bayesian approach, we calculated a posterior distribution of receiver operating characteristic area under the curve (ROC AUC) values, which allowed us to explicitly quantify the uncertainty in the quality of our predictions and to account for false negatives in the evaluation dataset. We found that wetland hydroperiod (the length of time that a wetland holds water) as well as the occurrence state in the prior year were generally the most important factors in determining occupancy. The model with only habitat covariates predicted species occurrences well; however, knowledge of wetland use in the previous year significantly improved predictive ability at the community level and for two of 12 species/species complexes. Our results demonstrate the utility of multi-species models for understanding which factors affect species habitat use of an entire community (of species) and provide an improved methodology using AUC that is helpful for quantifying the uncertainty in model predictions while explicitly accounting for detection biases.

Ecological Applications↗

USGS1996

A bayesian approach to classification criteria for spectacled eiders

To facilitate decisions to classify species according to risk of extinction, we used Bayesian methods to analyze trend data for the Spectacled Eider, an arctic sea duck. Trend data from three independent surveys of the Yukon-Kuskokwim Delta were analyzed individually and in combination to yield posterior distributions for population growth rates. We used classification criteria developed by the recovery team for Spectacled Eiders that seek to equalize errors of under- or overprotecting the species. We conducted both a Bayesian decision analysis and a frequentist (classical statistical inference) decision analysis. Bayesian decision analyses are computationally easier, yield basically the same results, and yield results that are easier to explain to nonscientists. With the exception of the aerial survey analysis of the 10 most recent years, both Bayesian and frequentist methods indicated that an endangered classification is warranted. The discrepancy between surveys warrants further research. Although the trend data are abundance indices, we used a preliminary estimate of absolute abundance to demonstrate how to calculate extinction distributions using the joint probability distributions for population growth rate and variance in growth rate generated by the Bayesian analysis. Recent apparent increases in abundance highlight the need for models that apply to declining and then recovering species.

Alaska↗

Refine your search to explore more results.