Geology topics

Tyler Wagner

Publications and source records attributed to Tyler Wagner.

At least 127 records · Page 7Linked to original sources

USGS2014

Importance of understanding landscape biases in USGS gage locations: Implications and solutions for managers

Flow and water temperature are fundamental properties of stream ecosystems upon which many freshwater resource management decisions are based. U.S. Geological Survey (USGS) gages are the most important source of streamflow and water temperature data available nationwide, but the degree to which gages represent landscape attributes of the larger population of streams has not been thoroughly evaluated. We identified substantial biases for seven landscape attributes in one or more regions across the conterminous United States. Streams with small watersheds (<10 km 2 ) and at high elevations were often underrepresented, and biases were greater for water temperature gages and in arid regions. Biases can fundamentally alter management decisions and at a minimum this potential for error must be acknowledged accurately and transparently. We highlight three strategies that seek to reduce bias or limit errors arising from bias and illustrate how one strategy, supplementing USGS data, can greatly reduce bias.

Fisheries↗

USGS2014

Spatial and temporal Brook Trout density dynamics: Implications for conservation, management, and monitoring

Many potential stressors to aquatic environments operate over large spatial scales, prompting the need to assess and monitor both site-specific and regional dynamics of fish populations. We used hierarchical Bayesian models to evaluate the spatial and temporal variability in density and capture probability of age-1 and older Brook Trout Salvelinus fontinalis from three-pass removal data collected at 291 sites over a 37-year time period (1975–2011) in Pennsylvania streams. There was high between-year variability in density, with annual posterior means ranging from 2.1 to 10.2 fish/100 m 2 ; however, there was no significant long-term linear trend. Brook Trout density was positively correlated with elevation and negatively correlated with percent developed land use in the network catchment. Probability of capture did not vary substantially across sites or years but was negatively correlated with mean stream width. Because of the low spatiotemporal variation in capture probability and a strong correlation between first-pass CPUE (catch/min) and three-pass removal density estimates, the use of an abundance index based on first-pass CPUE could represent a cost-effective alternative to conducting multiple-pass removal sampling for some Brook Trout monitoring and assessment objectives. Single-pass indices may be particularly relevant for monitoring objectives that do not require precise site-specific estimates, such as regional monitoring programs that are designed to detect long-term linear trends in density.

Pennsylvania↗

USGS2014

Evaluation of catch-and-release regulations on Brook Trout in Pennsylvania streams

In 2004, the Pennsylvania Fish and Boat Commission implemented catch-and-release (CR) regulations on headwater stream systems to determine if eliminating angler harvest would result in an increase in the number of adult (≥100 mm) or large (≥175 mm) Brook Trout Salvelinus fontinalis . Under the CR regulations, angling was permitted on a year-round basis, no Brook Trout could be harvested at any time, and there were no tackle restrictions. A before-after–control-impact design was used to evaluate the experimental regulations. Brook Trout populations were monitored in 16 treatment (CR regulations) and 7 control streams (statewide regulations) using backpack electrofishing gear periodically for up to 15 years (from 1990 to 2003 or 2004) before the implementation of the CR regulations and over a 7–8-year period (from 2004 or 2005 to 2011) after implementation. We used Poisson mixed models to evaluate whether electrofishing catch per effort (CPE; catch/100 m 2 ) of adult (≥100 mm) or large (≥175 mm) Brook Trout increased in treatment streams as a result of implementing CR regulations. Brook Trout CPE varied among sites and among years, and there was no significant effect (increase or decrease) of CR regulations on the CPE of adult or large Brook Trout. Results of our evaluation suggest that CR regulations were not effective at improving the CPE of adult or large Brook Trout in Pennsylvania streams. Low angler use, high voluntary catch and release, and slow growth rates in infertile headwater streams are likely the primary reasons for the lack of response.

Pennsylvania↗

USGS2014

A regional neural network model for predicting mean daily river water temperature

Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate and land use changes, thereby providing information that is valuable to management of river ecosystems and biota such as brook trout.

Journal of Hydrology↗

USGS2014

Cross-scale interactions: Quantifying multi-scaled cause–effect relationships in macrosystems

Ecologists are increasingly discovering that ecological processes are made up of components that are multi-scaled in space and time. Some of the most complex of these processes are cross-scale interactions (CSIs), which occur when components interact across scales. When undetected, such interactions may cause errors in extrapolation from one region to another. CSIs, particularly those that include a regional scaled component, have not been systematically investigated or even reported because of the challenges of acquiring data at sufficiently broad spatial extents. We present an approach for quantifying CSIs and apply it to a case study investigating one such interaction, between local and regional scaled land-use drivers of lake phosphorus. Ultimately, our approach for investigating CSIs can serve as a basis for efforts to understand a wide variety of multi-scaled problems such as climate change, land-use/land-cover change, and invasive species.

Frontiers in Ecology and the Environment↗

USGS2014

Approaches for advancing scientific understanding of macrosystems

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them.

Frontiers in Ecology and the Environment↗

USGS2014

Setting objectives for managing Key deer

The U.S. Fish and Wildlife Service (FWS) is responsible for the protection and management of Key deer ( Odocoileus virginianus clavium ) because the species is listed as Endangered under the Endangered Species Act (ESA). The purpose of the ESA is to protect and recover imperiled species and the ecosystems upon which they depend. There are a host of actions that could possibly be undertaken to recover the Key deer population, but without a clearly defined problem and stated objectives it can be difficult to compare and evaluate alternative actions. In addition, management goals and the acceptability of alternative management actions are inherently linked to stakeholders, who should be engaged throughout the process of developing a decision framework. The purpose of this project was to engage a representative group of stakeholders to develop a problem statement that captured the management problem the FWS must address with Key deer and identify objectives that, if met, would help solve the problem. In addition, the objectives were organized in a hierarchical manner (i.e., an objectives network) to show how they are linked, and measurable attributes were identified for each objective. We organized a group of people who represented stakeholders interested in and potentially affected by the management of Key deer. These stakeholders included individuals who represented local, state, and federal governments, non-governmental organizations, the general public, and local businesses. This stakeholder group met five full days over the course of an eight-week period to identify objectives that would address the following problem: “As recovery and removal from the Endangered Species list is the purpose of the Endangered Species Act, the U.S. Fish and Wildlife Service needs a management approach that will ensure a sustainable, viable, and healthy Key deer population. Urbanization has affected the behavior and population dynamics of the Key deer and the amount and characteristics of available habitat. The identified management approach must balance relevant social and economic concerns, Federal (e.g., Endangered Species Act, Wilderness Act, Refuge Act) and state regulations, and the conservation of biodiversity (e.g., Endangered/Threatened species, native habitat) in the Lower Keys.” The stakeholder group identified four fundamental objectives that are essential to addressing the problem: 1) Maximize a sustainable, viable, and healthy Key deer population, 2) Maximize value of Key deer to the People, 3) Minimize deer-related negative impacts to biodiversity, and 4) Minimize costs. In addition, the group identified 25 additional objectives that, if met, would help meet the fundamental objectives. The objectives network and measurable attributes identified by the stakeholder group can be used in the future to develop and evaluate potential management alternatives.

Cooperator Science Series↗

USGS2013

Detecting temporal change in freshwater fisheries surveys: statistical power and the important linkages between management questions and monitoring objectives

Monitoring to detect temporal trends in biological and habitat indices is a critical component of fisheries management. Thus, it is important that management objectives are linked to monitoring objectives. This linkage requires a definition of what constitutes a management-relevant “temporal trend.” It is also important to develop expectations for the amount of time required to detect a trend (i.e., statistical power) and for choosing an appropriate statistical model for analysis. We provide an overview of temporal trends commonly encountered in fisheries management, review published studies that evaluated statistical power of long-term trend detection, and illustrate dynamic linear models in a Bayesian context, as an additional analytical approach focused on shorter term change. We show that monitoring programs generally have low statistical power for detecting linear temporal trends and argue that often management should be focused on different definitions of trends, some of which can be better addressed by alternative analytical approaches.

Fisheries↗

USGS2013

Landscape-scale evaluation of asymmetric interactions between Brown Trout and Brook Trout using two-species occupancy models

Predicting the distribution of native stream fishes is fundamental to the management and conservation of many species. Modeling species distributions often consists of quantifying relationships between species occurrence and abundance data at known locations with environmental data at those locations. However, it is well documented that native stream fish distributions can be altered as a result of asymmetric interactions between dominant exotic and subordinate native species. For example, the naturalized exotic Brown Trout Salmo trutta has been identified as a threat to native Brook Trout Salvelinus fontinalis in the eastern United States. To evaluate large-scale patterns of co-occurrence and to quantify the potential effects of Brown Trout presence on Brook Trout occupancy, we used data from 624 stream sites to fit two-species occupancy models. These models assumed that asymmetric interactions occurred between the two species. In addition, we examined natural and anthropogenic landscape characteristics we hypothesized would be important predictors of occurrence of both species. Estimated occupancy for Brook Trout, from a co-occurrence model with no landscape covariates, at sites with Brown Trout present was substantially lower than sites where Brown Trout were absent. We also observed opposing patterns for Brook and Brown Trout occurrence in relation to percentage forest, impervious surface, and agriculture within the network catchment. Our results are consistent with other studies and suggest that alterations to the landscape, and specifically the transition from a forested catchment to one that contains impervious surface or agriculture, reduces the occurrence probability of wild Brook Trout. Our results, however, also suggest that the presence of Brown Trout results in lower occurrence probability of Brook Trout over a range of anthropogenic landscape characteristics, compared with streams where Brown Trout were absent.

Pennsylvania↗

USGS2012

Estimating spatial and temporal components of variation in count data using negative binomial mixed models

P artitioning total variability into its component temporal and spatial sources is a powerful way to better understand time series and elucidate trends. The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes Sander vitreus across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site × year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.

Iowa, Maine, Michigan, Ohio, Wisconsin↗

USGS2012

Can migration mitigate the effects of ecosystem change? Patterns of dispersal, energy acquisition and allocation in Great Lakes lake whitefish (Coregonus clupeaformis)

Migration can be a behavioural response to poor or declining home range habitat quality and can occur when the costs of migration are overcome by the benefi ts of encountering higher-quality resources elsewhere. Despite dramatic ecosystem-level changes in the benthic food web of the Laurentian Great Lakes since the colonization of dreissenid mussels, coincident changes in condition and growth rates among benthivorous lake whitefi sh populations have been variable. We hypothesized that this variation could be in part mitigated by differences in migratory habits among populations, where increased migration distance can result in an increased probability of encountering high-quality habitat (relative to the home range). Results from four Great Lakes populations support this hypothesis; relative growth rates increased regularly with migration distance. The population with the largest average migration distance also had the least reduction in size-at-age during a period of signifi cant ecosystem change and among the highest estimated consumption and activity rates. In comparison, the population with the greatest declines in size-at-age was among the least mobile, demonstrating only moderate rates of consumption and activity. The least mobile population of lake whitefi sh was supported by a remnant Diporeia population and has experienced only moderate temporal growth declines. Our study provides evidence for the potential role of migration in mitigating the effects of ecosystem change on lake whitefi sh populations.

Great Lakes↗

USGS2011

Landscape drivers of regional variation in the relationship between total phosphorus and chlorophyll in lakes

1. For north temperate lakes, the well-studied empirical relationship between phosphorus (as measured by total phosphorus, TP), the most commonly limiting nutrient and algal biomass (as measured by chlorophyll a , CHL) has been found to vary across a wide range of landscape settings. Variation in the parameters of these TP–CHL regressions has been attributed to such lake variables as nitrogen/phosphorus ratios, organic carbon and alkalinity, all of which are strongly related to catchment characteristics (e.g. natural land cover and human land use). Although this suggests that landscape setting can help to explain much of the variation in ecoregional TP–CHL regression parameters, few studies have attempted to quantify relationships at an ecoregional spatial scale. 2. We tested the hypothesis that lake algal biomass and its predicted response to changes in phosphorus are related to both local-scale features (e.g. lake and catchment) and ecoregional-scale features, all of which affect the availability and transport of covarying solutes such as nitrogen, organic carbon and alkalinity. Specifically, we expected that land use and cover, acting at both local and ecoregional scales, would partially explain the spatial pattern in parameters of the TP–CHL regression. 3. We used a multilevel modelling framework and data from 2105 inland lakes spanning 35 ecoregions in six US states to test our hypothesis and identify specific local and ecoregional features that explain spatial heterogeneity in TP–CHL relationships. We include variables such as lake depth, natural land cover (for instance, wetland cover in the catchment of lakes and in the ecoregions) and human land use (for instance, agricultural land use in the catchment of lakes and in the ecoregions). 4. There was substantial heterogeneity in TP–CHL relationships across the 35 ecoregions. At the local scale, CHL was negatively and positively related to lake mean depth and percentage of wooded wetlands in the catchment, respectively. At the ecoregional scale, the slope parameter was positively related to the percentage of pasture in an ecoregion, indicating that CHL tends to respond more rapidly to changes in TP where there are high levels of agricultural pasture than where there is little. The intercept (i.e. the ecoregion-average CHL) was negatively related to the percentage of wooded wetlands in the ecoregion. 5. By explicitly accounting for the hierarchical nature of lake–landscape interactions, we quantified the effects of landscape characteristics on the response of CHL to TP at two spatial scales. We provide new insight into ecoregional drivers of the rate at which algal biomass responds to changes in nutrient concentrations. Our results also indicate that the direction and magnitude of the effects of certain land use and cover characteristics on lake nutrient dynamics may be scale dependent and thus likely to represent different underlying mechanisms regulating lake productivity.

Freshwater Biology↗

USGS2011

Evaluation of hypotheses for explaining temporal trends in Atlantic salmon parr densities in Northeast U.S. Rivers

Atlantic salmon Salmo salar in the USA have declined dramatically and their persistence is heavily dependent on stocking juvenile fish, predominantly fry. The success of stocking hatchery fry is evaluated annually throughout New England by electrofishing surveys targeting age-1 parr. The objective of this study was to examine temporal trends in Atlantic salmon parr densities throughout New England and determine how trends vary among river basins. We fit generalized additive mixed models to investigate potential linear and nonlinear temporal trends in parr density. Akaike's information criterion was used to evaluate competing hypotheses about how temporal trends vary regionally. The top-ranked model suggested two types of trends. The first type (the Penobscot River) showed a nonlinear trend in which parr densities increased until the 1990s and then rapidly decreased through 2008. The second type (all other rivers) showed a linear decrease throughout the time series. Parr density trends reflected trends in spawning escapement for each river group. We conclude that fry stocking has not been able to overcome the decrease in spawning escapement in altered stream ecosystems in New England and that additional management strategies should be considered.

North American Journal of Fisheries Management↗

USGS2011

Using multilevel models to quantify heterogeneity in resource selection

Models of resource selection are being used increasingly to predict or model the effects of management actions rather than simply quantifying habitat selection. Multilevel, or hierarchical, models are an increasingly popular method to analyze animal resource selection because they impose a relatively weak stochastic constraint to model heterogeneity in habitat use and also account for unequal sample sizes among individuals. However, few studies have used multilevel models to model coefficients as a function of predictors that may influence habitat use at different scales or quantify differences in resource selection among groups. We used an example with white-tailed deer ( Odocoileus virginianus ) to illustrate how to model resource use as a function of distance to road that varies among deer by road density at the home range scale. We found that deer avoidance of roads decreased as road density increased. Also, we used multilevel models with sika deer ( Cervus nippon ) and white-tailed deer to examine whether resource selection differed between species. We failed to detect differences in resource use between these two species and showed how information-theoretic and graphical measures can be used to assess how resource use may have differed. Multilevel models can improve our understanding of how resource selection varies among individuals and provides an objective, quantifiable approach to assess differences or changes in resource selection.

Journal of Wildlife Management↗

USGS2010

Behavioral response of manatees to variations in environmental sound levels

Florida manatees ( Trichechus manatus latirostris ) inhabit coastal regions because they feed on the aquatic vegetation that grows in shallow waters, which are the same areas where human activities are greatest. Noise produced from anthropogenic and natural sources has the potential to affect these animals by eliciting responses ranging from mild behavioral changes to extreme aversion. Sound levels were calculated from recordings made throughout behavioral observation periods. An information theoretic approach was used to investigate the relationship between behavior patterns and sound level. Results indicated that elevated sound levels affect manatee activity and are a function of behavioral state. The proportion of time manatees spent feeding and milling changed in response to sound level. When ambient sound levels were highest, more time was spent in the directed, goal-oriented behavior of feeding, whereas less time was spent engaged in undirected behavior such as milling. This work illustrates how shifts in activity of individual manatees may be useful parameters for identifying impacts of noise on manatees and might inform population level effects.

Marine Mammal Science↗

USGS2010

Spatial and temporal dynamics of lake whitefish (Coregonus clupeaformis) health indicators: linking individual-based indicators to a management-relevant endpoint

We examined the spatial and temporal dynamics of health indicators in four lake whitefish ( Coregonus clupeaformis ) stocks located in northern lakes Michigan and Huron from 2003 to 2006. The specific objectives were to (1) quantify spatial and temporal variability in health indicators; (2) examine relationships among nutritional indicators and stock-specific spatial and temporal dynamics of pathogen prevalence and intensity of infection; and (3) examine relationships between indicators measured on individual fish and stock-specific estimates of natural mortality. The percent of the total variation attributed to spatial and temporal sources varied greatly depending on the health indicator examined. The most notable pattern was a downward trend in the concentration of highly unsaturated fatty acids (HUFAs), observed in all stocks, in the polar lipid fraction of lake whitefish dorsal muscle tissue over the three study years. Variation among stocks and years for some indicators were correlated with the prevalence and intensity of the swimbladder nematode Cystidicola farionis , suggesting that our measures of fish health were related, at some level, with disease dynamics. We did not find relationships between spatial patterns in fish health indicators and estimates of natural mortality rates for the stocks. Our research highlights the complexity of the interactions between fish nutritional status, disease dynamics, and natural mortality in wild fish populations. Additional research that identifies thresholds of health indicators, below (or above) which survival may be reduced, will greatly help in understanding the relationship between indicators measured on individual fish and potential population-level effects.

Michigan↗

USGS2010

Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation

Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

Iowa, Maine, Michigan, Ohio, Wisconsin↗

USGS2009

Evaluating the power to detect temporal trends in fishery independent surveys: A case study based on Gillnets Set in the Ohio waters of Lake Erie for walleye

Fishery-independent (FI) surveys provide critical information used for the sustainable management and conservation of fish populations. Because fisheries management often requires the effects of management actions to be evaluated and detected within a relatively short time frame, it is important that research be directed toward FI survey evaluation, especially with respect to the ability to detect temporal trends. Using annual FI gill-net survey data for Lake Erie walleyes Sander vitreus collected from 1978 to 2006 as a case study, our goals were to (1) highlight the usefulness of hierarchical models for estimating spatial and temporal sources of variation in catch per effort (CPE); (2) demonstrate how the resulting variance estimates can be used to examine the statistical power to detect temporal trends in CPE in relation to sample size, duration of sampling, and decisions regarding what data are most appropriate for analysis; and (3) discuss recommendations for evaluating FI surveys and analyzing the resulting data to support fisheries management. This case study illustrated that the statistical power to detect temporal trends was low over relatively short sampling periods (e.g., 5–10 years) unless the annual decline in CPE reached 10–20%. For example, if 50 sites were sampled each year, a 10% annual decline in CPE would not be detected with more than 0.80 power until 15 years of sampling, and a 5% annual decline would not be detected with more than 0.8 power for approximately 22 years. Because the evaluation of FI surveys is essential for ensuring that trends in fish populations can be detected over management-relevant time periods, we suggest using a meta-analysis–type approach across systems to quantify sources of spatial and temporal variation. This approach can be used to evaluate and identify sampling designs that increase the ability of managers to make inferences about trends in fish stocks.

Ohio↗