Geology topics

Brian J. Irwin

Publications and source records attributed to Brian J. Irwin.

28 records · Page 2Linked to original sources

USGS2017

Using variance structure to quantify responses to perturbation in fish catches

We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

Transactions of the American Fisheries Society↗

USGS2016

Transboundary fisheries science: Meeting the challenges of inland fisheries management in the 21st century

Managing inland fisheries in the 21st century presents several obstacles, including the need to view fisheries from multiple spatial and temporal scales, which usually involves populations and resources spanning sociopolitical boundaries. Though collaboration is not new to fisheries science, inland aquatic systems have historically been managed at local scales and present different challenges than in marine or large freshwater systems like the Laurentian Great Lakes. Therefore, we outline a flexible strategy that highlights organization, cooperation, analytics, and implementation as building blocks toward effectively addressing transboundary fisheries issues. Additionally, we discuss the use of Bayesian hierarchical models (within the analytical stage), due to their flexibility in dealing with the variability present in data from multiple scales. With growing recognition of both ecological drivers that span spatial and temporal scales and the subsequent need for collaboration to effectively manage heterogeneous resources, we expect implementation of transboundary approaches to become increasingly critical for effective inland fisheries management.

Fisheries↗

USGS2016

Adapting inland fisheries management to a changing climate

Natural resource decision makers are challenged to adapt management to a changing climate while balancing short-term management goals with long-term changes in aquatic systems. Adaptation will require developing resilient ecosystems and resilient management systems. Decision makers already have tools to develop or ensure resilient aquatic systems and fisheries such as managing harvest and riparian zones. Because fisheries management often interacts with multiple stakeholders, adaptation strategies involving fisheries managers and other partners focused on land use, policy, and human systems, coupled with long-term monitoring, are necessary for resilient systems. We show how agencies and organizations are adapting to a changing climate in Minnesota and Ontario lakes and Montana streams. We also present how the Florida Fish and Wildlife Commission created a management structure to develop adaptation strategies. These examples demonstrate how organizations and agencies can cope with climate change effects on fishes and fisheries through creating resilient management and ecological systems.

Fisheries↗

USGS2016

Management strategy evaluation of pheromone-baited trapping techniques to improve management of invasive sea lamprey

We applied a management strategy evaluation (MSE) model to examine the potential cost-effectiveness of using pheromone-baited trapping along with conventional lampricide treatment to manage invasive sea lamprey. Four pheromone-baited trapping strategies were modeled: (1) stream activation wherein pheromone was applied to existing traps to achieve 10 −12 mol/L in-stream concentration, (2) stream activation plus two additional traps downstream with pheromone applied at 2.5 mg/hr (reverse-intercept approach), (3) trap activation wherein pheromone was applied at 10 mg/hr to existing traps, and (4) trap activation and reverse-intercept approach. Each new strategy was applied, with remaining funds applied to conventional lampricide control. Simulating deployment of these hybrid strategies on fourteen Lake Michigan streams resulted in increases of 17 and 11% (strategies 1 and 2) and decreases of 4 and 7% (strategies 3 and 4) of the lakewide mean abundance of adult sea lamprey relative to status quo. MSE revealed performance targets for trap efficacy to guide additional research because results indicate that combining lampricides and high efficacy trapping technologies can reduce sea lamprey abundance on average without increasing control costs.

Natural Resource Modeling↗

USGS2016

Using GPS telemetry to determine roadways most susceptible to deer-vehicle collisions

More than 1 million wildlife-vehicle collisions occur annually in the United States. The majority of these accidents involve white-tailed deer (Odocoileus virginianus) and result in >US $4.6 billion in damage and >200 human fatalities. Prior research has used collision locations to assess sitespecific as well as landscape features that contribute to risk of deer-vehicle collisions. As an alternative approach, we calculated road-crossing locations from 25 GPS-instrumented white-tailed deer near Madison, Georgia (n=154,131 hourly locations). We identified crossing locations by creating movement paths between subsequent GPS points and then intersecting the paths with road locations. Using AIC model selection, we determined whether 10 local and landscape variables were successful at identifying areas where higher frequencies of deer crossings were likely to occur. Our findings indicate that traffic volume, distance to riparian areas, and the amount of forested area influenced the frequency of road crossings. Roadways that were predominately located in wooded landscapes and 200–300 m from riparian areas were crossed frequently. Additionally, we found that areas of low traffic volume (e.g., county roads) had the highest frequencies of deer crossings. Analyses utilizing only records of deer-vehicle collision locations cannot separate the relative contribution of deer crossing rates and traffic volume. Increased frequency of road crossings by deer in low-traffic, forested areas may lead to a greater risk of deer-vehicle collision than suggested by evaluations of deer-vehicle collision frequency alone.

Georgia↗

USGS2014

Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of the Vital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year −1 for all indicators and is appropriate for detecting a 1 % trend·year −1 in most indicators.

New Jersey, Pennsylvania, Virginia, West Virginia↗

USGS2014

Impact of increasing market access on a tropical small-scale fishery

Small-scale fisheries have historically been marginalized in management and policy investments, and they often remain under-reported in national economic and fisheries statistics. Even so, small-scale fisheries are not entirely buffered from the impacts of globalization, such as the introduction and expansion of markets. This study measures the long-term impact of market-access on a coastal fishery on Nicaragua׳s remote Atlantic Coast from approximately the time when fishermen had access to stable and predictable local markets until the present, when the region has been transformed by road connection. In the last four years, fisheries trade has expanded as road connection has facilitated export to distant markets. Fishery-independent surveys were used to measure changes in indicators of fish-community status such as length-frequency, mean trophic level, and relative biomass. Species-level changes in relative biomass of common snook Centropomus undecimalis and gafftopsail catfish Bagre marinus were also evaluated since these species are the most economically valuable and likely account for the most fish biomass in the system. Using historical records, reports, current observations and interviews, changes in indicators of fishing intensity and market access over the past 17 years were assessed. From 1994 to 2011, community and species-specific metrics of the lagoon fishery declined significantly across all indicators examined. The potential social and economic outcomes of the decline in the fishery are far-reaching for the region, because this tropical fishery comprises the main source of protein and income for residents of twelve indigenous and Afro-descendent communities.

Marine Policy↗

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

Consideration of reference points for the management of renewable resources under an adaptive management paradigm

The success of natural resource management depends on monitoring, assessment and enforcement. In support of these efforts, reference points (RPs) are often viewed as critical values of management-relevant indicators. This paper considers RPs from the standpoint of objective-driven decision making in dynamic resource systems, guided by principles of structured decision making (SDM) and adaptive resource management (AM). During the development of natural resource policy, RPs have been variously treated as either ‘targets’ or ‘triggers’. Under a SDM/AM paradigm, target RPs correspond approximately to value-based objectives, which may in turn be either of fundamental interest to stakeholders or intermediaries to other central objectives. By contrast, trigger RPs correspond to decision rules that are presumed to lead to desirable outcomes (such as the programme targets). Casting RPs as triggers or targets within a SDM framework is helpful towards clarifying why (or whether) a particular metric is appropriate. Further, the benefits of a SDM/AM process include elucidation of underlying untested assumptions that may reveal alternative metrics for use as RPs. Likewise, a structured decision-analytic framework may also reveal that failure to achieve management goals is not because the metrics are wrong, but because the decision-making process in which they are embedded is insufficiently robust to uncertainty, is not efficiently directed at producing a resource objective, or is incapable of adaptation to new knowledge.

Environmental Conservation↗

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↗