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At least 37 records · Page 2Linked to original sources
USGS2021

Can identifying discrete behavioral groups with individual-based acoustic telemetry advance the understanding of fish distribution patterns?

Identifying patterns of organismal distribution can provide valuable insights for basic and applied marine and coastal ecology because understanding where animals are located is foundational to both research and science-based conservation. Understanding variation in distributional patterns can lead to a better assessment of ecological drivers and an improved ability to predict consequences of natural and altered relationships. Here, our purpose is to explore if quantifying coexisting groups of individual fish predators advances our understanding of field distribution patterns. Toward this end, we quantified locations of 59 acoustically tagged striped bass ( Morone saxatilis) within a 26-stationary unit telemetry receiver array in Plum Island Estuary (PIE), MA, United States. We then used cluster analyses on spatial and temporal-spatial metrics from this dataset to (1) assess if distinct groups of individuals coexisted, (2) quantify group characteristics, and (3) test associations between groups and distribution (e.g., physical site type and region). Based on multiple lines of evidence, we identified four groups of striped bass with different space use patterns that persisted across seasons (summer and fall). Similar-sized striped bass clustered at spatial and temporal scales at which individuals within distinct groups could, and did, physically overlap. In addition, distributional groups were linked to components of physical site type and region suggesting that discrete groups of individuals can interact differently with the environment within the same ecological system. The identification of these distinct groups of individuals creates a baseline from which to explore further ecological implications of grouping behavior for research and conservation in geographically large, temporally dynamic, and spatially heterogeneous marine and coastal environments.

Massachusetts↗
USGS2006

The fitting of general force-of-infection models to wildlife disease prevalence data

Researchers and wildlife managers increasingly find themselves in situations where they must deal with infectious wildlife diseases such as chronic wasting disease, brucellosis, tuberculosis, and West Nile virus. Managers are often charged with designing and implementing control strategies, and researchers often seek to determine factors that influence and control the disease process. All of these activities require the ability to measure some indication of a disease's foothold in a population and evaluate factors affecting that foothold. The most common type of data available to managers and researchers is apparent prevalence data. Apparent disease prevalence, the proportion of animals in a sample that are positive for the disease, might seem like a natural measure of disease's foothold, but several properties, in particular, its dependency on age structure and the biasing effects of disease-associated mortality, make it less than ideal. In quantitative epidemiology, the a??force of infection,a?? or infection hazard, is generally the preferred parameter for measuring a disease's foothold, and it can be viewed as the most appropriate way to a??adjusta?? apparent prevalence for age structure. The typical ecology curriculum includes little exposure to quantitative epidemiological concepts such as cumulative incidence, apparent prevalence, and the force of infection. The goal of this paper is to present these basic epidemiological concepts and resulting models in an ecological context and to illustrate how they can be applied to understand and address basic epidemiological questions. We demonstrate a practical approach to solving the heretofore intractable problem of fitting general force-of-infection models to wildlife prevalence data using a generalized regression approach. We apply the procedures to Mycobacterium bovis (bovine tuberculosis) prevalence in bison (Bison bison) in Wood Buffalo National Park, Canada, and demonstrate strong age dependency in the force of infection as well as an increased mortality hazard in positive animals.

Ecology↗
USGS2013

Beaver dams maintain fish biodiversity by increasing habitat heterogeneity throughout a low-gradient stream network

Understanding the relationship between heterogeneity and biodiversity is an active focus of ecological research. Although habitat heterogeneity is conceptually linked to biodiversity, the amount and configuration of heterogeneity that maintains biodiversity within ecosystems is not well understood, especially for an entire stream network. Here, we tested alternative outcomes about how habitat alterations caused by beaver dams affected native fish biodiversity. Specifically, we quantified in-stream habitat and fish assemblages above and below all beaver dams ( n = 15) and selected control sites ( n = 9), adjacent to beaver dams, within an entire, low-gradient stream network (Fish Brook, MA, U.S.A.). Beaver dams altered habitat within streams in four ways based on upstream versus downstream differences in stream width, depth, velocity and substratum. In general, habitat heterogeneity, measured using two indices, was greater at beaver dams than control sites. The diversity and abundance of fish around beaver dams were positively related to habitat heterogeneity. Faster water and the coarser substratum below beaver dams increased the amount of fluvial habitat available to native fish. This alteration can be critical for fish with life histories that depend on flowing water and hard substrata. In summary, within a stream network, beaver dams maintained fish biodiversity by altering in-stream habitat and increasing habitat heterogeneity. Understanding the relationship between habitat heterogeneity and biodiversity can advance basic freshwater ecology and provide science-based support for applied aquatic conservation

Massachusetts↗
USGS2024

Designing count-based studies in a world of hierarchical models

Advances in hierarchical modeling have improved estimation of ecological parameters from count data, especially those quantifying population abundance, distribution, and dynamics by explicitly accounting for observation processes, particularly incomplete detection. Even hierarchical models that account for incomplete detection, however, cannot compensate for data limitations stemming from poorly planned sampling. Ecologists therefore need guidance for planning count-based studies that follow established sampling theory, collect appropriate data, and apply current modeling approaches to answer their research questions. We synthesize available literature relevant to guiding count-based studies. Considering the central historical and ongoing contributions of avian studies to ecological knowledge, we focus on birds as a case study for this review, but the basic principles apply to all populations whose members are sufficiently observable to be counted. The sequence of our review represents the thought process in which we encourage ecologists to engage 1) the research question(s) and population parameters to measure, 2) sampling design, 3) analytical framework, 4) temporal design, and 5) survey protocol. We also provide 2 hypothetical demonstrations of these study plan components representing different research questions and study systems. Mirroring the structure of hierarchical models, we suggest researchers primarily focus on the ecological processes of interest when designing their approach to sampling, and wait to consider logistical constraints of data collection and observation processes when developing the survey protocol. We offer a broad framework for researchers planning count-based studies, while pointing to relevant literature elaborating on particular tools and concepts.

Journal of Wildlife Management↗
USGS2022

Medium spatial resolution mapping of global land cover and land cover change across multiple decades from Landsat

Land cover maps are essential for characterizing the biophysical properties of the Earth’s land areas. Because land cover information synthesizes a rich array of information related to both the ecological condition of land areas and their exploitation by humans, they are widely used for basic and applied research that requires information related to land surface properties (e.g., terrestrial carbon models, water balance models, weather, and climate models) and are core inputs to models and analyses used by natural resource scientists and land managers. As the Earth’s global population has grown over the last several decades rates of land cover change have increased dramatically, with enormous impacts on ecosystem services (e.g., biodiversity, water supply, carbon sequestration, etc.). Hence, accurate information related to land cover is essential for both managing natural resources and for understanding society’s ecological, biophysical, and resource management footprint. To address the need for high-quality land cover information we are using the global record of Landsat observations to compile annual maps of global land cover from 2001 to 2020 at 30 m spatial resolution. To create these maps we use features derived from time series of Landsat imagery in combination with ancillary geospatial data and a large database of training sites to classify land cover at annual time step. The algorithm that we apply uses temporal segmentation to identify periods with stable land cover that are separated by breakpoints in the time series. Here we provide an overview of the methods and data sets we are using to create global maps of land cover. We describe the algorithms used to create these maps and the core land cover data sets that we are creating through this effort, and we summarize our approach to accuracy assessment. We also present a synthesis of early results and discuss the strengths and weaknesses of our early map products and the challenges that we have encountered in creating global land cover data sets from Landsat. Initial accuracy assessment for North America shows good overall accuracy (77.0 ± 2.0% correctly classified) and 79.8% agreement with the European Space Agency (ESA) WorldCover product. The land cover mapping results we report provide the foundation for robust, repeatable, and accurate mapping of global land cover and land cover change across multiple decades at 30 m spatial resolution from Landsat.

Frontiers in Remote Sensing↗
USGS2016

Combining statistical inference and decisions in ecology

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation, and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem.

Ecological Applications↗
USGS2014

Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations

Many applications in ecological genetics involve sampling individuals from a mixture of multiple biological populations and subsequently associating those individuals with the populations from which they arose. Analytical methods that assign individuals to their putative population of origin have utility in both basic and applied research, providing information about population-specific life history and habitat use, ecotoxins, pathogen and parasite loads, and many other non-genetic ecological, or phenotypic traits. Although the question is initially directed at the origin of individuals, in most cases the ultimate desire is to investigate the distribution of some trait among populations. Current practice is to assign individuals to a population of origin and study properties of the trait among individuals within population strata as if they constituted independent samples. It seemed that approach might bias population-specific trait inference. In this study we made trait inferences directly through modeling, bypassing individual assignment. We extended a Bayesian model for population mixture analysis to incorporate parameters for the phenotypic trait and compared its performance to that of individual assignment with a minimum probability threshold for assignment. The Bayesian mixture model outperformed individual assignment under some trait inference conditions. However, by discarding individuals whose origins are most uncertain, the individual assignment method provided a less complex analytical technique whose performance may be adequate for some common trait inference problems. Our results provide specific guidance for method selection under various genetic relationships among populations with different trait distributions.

PLoS ONE↗
USGS2017

The Wetland and Aquatic Research Center strategic science plan

Introduction The U.S. Geological Survey (USGS) Wetland and Aquatic Research Center (WARC) has two primary locations (Gainesville, Florida, and Lafayette, Louisiana) and field stations throughout the southeastern United States and Caribbean. WARC’s roots are in U.S. Fish and Wildlife Service (USFWS) and National Park Service research units that were brought into the USGS as the Biological Research Division in 1996. Founded in 2015, WARC was created from the merger of two long-standing USGS biology science Centers—the Southeast Ecological Science Center and the National Wetlands Research Center—to bring together expertise in biology, ecology, landscape science, geospatial applications, and decision support in order to address issues nationally and internationally. WARC scientists apply their expertise to a variety of wetland and aquatic research and monitoring issues that require coordinated, integrated efforts to better understand natural environments. By increasing basic understanding of the biology of important species and broader ecological and physiological processes, this research provides information to policymakers and aids managers in their stewardship of natural resources and in regulatory functions. This strategic science plan (SSP) was developed to guide WARC research during the next 5–10 years in support of Department of the Interior (DOI) partnering bureaus such as the USFWS, the National Park Service, and the Bureau of Ocean Energy Management, as well as other Federal, State, and local natural resource management agencies. The SSP demonstrates the alignment of the WARC goals with the USGS mission areas, associated programs, and other DOI initiatives. The SSP is necessary for workforce planning and, as such, will be used as a guide for future needs for personnel. The SSP also will be instrumental in developing internal funding priorities and in promoting WARC’s capabilities to both external cooperators and other groups within the USGS.

Open-File Report↗
USGS2010

Landscape genetics of high mountain frog metapopulations

Explaining functional connectivity among occupied habitats is crucial for understanding metapopulation dynamics and species ecology. Landscape genetics has primarily focused on elucidating how ecological features between observations influence gene flow. Functional connectivity, however, may be the result of both these between‐site (landscape resistance) landscape characteristics and at‐site (patch quality) landscape processes that can be captured using network based models. We test hypotheses of functional connectivity that include both between‐site and at‐site landscape processes in metapopulations of Columbia spotted frogs ( Rana luteiventris ) by employing a novel justification of gravity models for landscape genetics (eight microsatellite loci, 37 sites, n = 441). Primarily used in transportation and economic geography, gravity models are a unique approach as flow (e.g. gene flow) is explained as a function of three basic components: distance between sites, production/attraction (e.g. at‐site landscape process) and resistance (e.g. between‐site landscape process). The study system contains a network of nutrient poor high mountain lakes where we hypothesized a short growing season and complex topography between sites limit R. luteiventris gene flow. In addition, we hypothesized production of offspring is limited by breeding site characteristics such as the introduction of predatory fish and inherent site productivity. We found that R. luteiventris connectivity was negatively correlated with distance between sites, presence of predatory fish (at‐site) and topographic complexity (between‐site). Conversely, site productivity (as measured by heat load index, at‐site) and growing season (as measured by frost‐free period between‐sites) were positively correlated with gene flow. The negative effect of predation and positive effect of site productivity, in concert with bottleneck tests, support the presence of source–sink dynamics. In conclusion, gravity models provide a powerful new modelling approach for examining a wide range of both basic and applied questions in landscape genetics.

Idaho↗
USGS2020

Vegetation sampling and management

What is the utility of vegetation measurements for wildlife managers? In the prairie, savanna, tundra, forest, steppe, and wetland regions of the world, mixtures of plant species provide wildlife with food, cover and, in some circumstances, water; the 3 essential habitat elements necessary to sustain viable wildlife populations. We define habitat in reference to use of a vegetation type by an animal (e.g., deer habitat) and vegetation type when referring to differences in vegetation stands (e.g., marsh vegetation type versus tall grass prairie vegetation type; Hall et al. 1997). In strict definition, the variety of wildlife using plants ranges from snails and voles (Microtus spp.) to bison (Bison bison) and elephants (Loxodonta spp.) in uplands and from mosquitoes and ducks to muskrats (Ondatra zibethicus) and manatees (Trichechus manatus) in wetlands. Through evolutionary processes, some wildlife species are totally dependent on vegetation for all annual life requirements, whereas other species use vegetation only for cover or food. Regardless of the role of vegetation in the sustenance of wildlife, any management or research project that requires evaluation of wildlife and vegetation type relationships on a unit of land will necessitate some form of vegetation measurement. The term vegetation can refer to a single plant or species on a specific site or a community in the landscape. Vegetation may occur naturally or be introduced, and may be live or dead. Uses of vegetation measurements are many: (1) evaluation of vegetation response to management practices, (2) estimation of carrying capacity and/or forage production, (3) characterization of cover and habitat components for an endangered species, or (4) long-term monitoring of the general trend of plant vigor or vegetation type condition. Surveying and measuring quantity and quality of vegetation within habitats are basic to wildlife research and management. Grassland, shrubland, and woodland vegetation types are comprised of populations in which individual plants are usually too numerous to inventory completely. Consequently, wildlife biologists usually use sampling techniques to make inferences about the total plant population within a given vegetation type. Vegetation sampling methodologies have evolved within several ecological disciplines (e.g., plant ecology, forestry, rangeland science) and for a variety of management or research objectives (e.g., estimating forage for ungulates, describing habitat use by passerine birds). Description of every method that has been used to sample vegetation is beyond the scope of this chapter. We describe how to measure vegetation structure, which Dansereau (1957) defined as the spatial organization (distribution) of individuals that form a stand. We have organized this chapter into a description of basic methods of vegetation sampling with examples of how those methods have been applied or modified in wildlife research and management. We assume the investigator/reader has adequate knowledge of the concepts of wildlife ecology, primary habitat requirements of wildlife species under study, and ability to systematically identify the species of wildlife and vascular plants within the geographical area of investigation.

Book chapter↗
USGS2014

USGS ecosystem research for the next decade: advancing discovery and application in parks and protected areas through collaboration

Ecosystems within parks and protected areas in the United States and throughout the world are being transformed at an unprecedented rate. Changes associated with natural hazards, greenhouse gas emissions, and increasing demands for water, food, land, energy and mineral resources are placing urgency on sound decision making that will help sustain our Nation’s economic and environmental well-being (Millennium Ecosystem Assessment, 2005). In recognition of the importance of science in making these decisions, the U.S. Geological Survey (USGS) in 2007 identified ecosystem science as one of six science directions included in a comprehensive decadal strategy (USGS 2007). The Ecosystems Mission Area was identified as essential for integrating activity within the USGS and as a key to enhanced integration with other Federal and private sector research and management organizations (Myers at al., 2007). This paper focuses on benefits to parks and protected areas from the USGS Ecosystems Mission Area plan that expanded the scope of the original 2007 science strategy, to identify the Bureau’s work in ecosystem science over the next decade (Williams et al., 2013). The plan describes a framework that encompasses both basic and applied science and allows the USGS to continue to contribute meaningfully to conservation and management issues related to the Nation’s parks and ecological resources. This framework relies on maintaining long-standing, collaborative relationships with partners in both conducting science and applying scientific results. Here we summarize the major components of the USGS Ecosystems Science Strategy, articulating the vision, goals and strategic approaches, then outlining some of the proposed actions that will ultimately prove useful to those managing parks and protected areas. We end with a discussion on the future of ecosystem science for the USGS and how it can be used to evaluate ecosystem change and the associated consequences to management of our Nation’s natural resources.

The George Wright Forum↗
USGS2009

Maintaining the competitiveness of the American Fisheries Society journals: An assessment based on influence and cost-effectiveness

Recent changes in the landscape of scientific publishing prompted the Publications Overview Committee of the American Fisheries Society (AFS) to review the Society's portfolio of scientific journals. We evaluated journals based on metrics in two categories: (1) citation-based measures of the influence of a journal on the scientific literature, and (2) measures of the cost-effectiveness of a journal (citation rate adjusted for subscription cost). Over the long-term, we found that ecology journals had far stronger citation-based influence than fisheries and aquatic sciences journals, and that journals publishing primarily basic research had stronger influence than journals publishing applied research (including four AFS journals and Fisheries magazine). In evaluating the current status of fisheries and aquatic sciences journals, we found that metrics of influence and cost-effectiveness provided considerably different portrayals of journals relative to their peers. In terms of citation-based influence, we found that the AFS journal Transactions of the American Fisheries Society (TAFS) and Fisheries magazine were competitive with highly regarded peer fisheries journals, but that North American Journal of Aquaculture (NAJA) and Journal of Aquatic Animal Health (JAAH) were less influential than their peers. The citation-based influence of North American Journal of Fisheries Management (NAJFM) was intermediate between TAFS/Fisheries and NAJA/JAAH . For journals like NAJFM and NAJA , we expect that much of the scientific influence on policy and management is not captured by citations in the primary literature, and alternative methods of evaluation may be needed. All of the AFS journals ranked highly with regard to cost-effectiveness because their subscription costs are low, and these rankings are in accordance with membership needs and the strategic mission of AFS to provide broad and timely dissemination of scientific information. We conclude by suggesting ways to increase the influence of AFS journals without compromising their accessibility and affordability, and offer advice about methods and frequency for future journal evaluations.

Fisheries↗
USGS2021

Evaluating natural experiments in ecology: Using synthetic controls in assessments of remotely sensed land treatments

Many important ecological phenomena occur on large spatial scales and/or are unplanned and thus do not easily fit within analytical frameworks that rely on randomization, replication, and interspersed a priori controls for statistical comparison. Analyses of such large‐scale, natural experiments are common in the health and econometrics literature, where techniques have been developed to derive insight from large, noisy observational data sets. Here, we apply a technique from this literature, synthetic control, to assess landscape change with remote sensing data. The basic data requirements for synthetic control include (1) a discrete set of treated and untreated units, (2) a known date of treatment intervention, and (3) time series response data that include both pre‐ and post‐treatment outcomes for all units. Synthetic control generates a response metric for treated units relative to a no‐action alternative based on prior relationships between treated and unexposed groups. Using simulations and a case study involving a large‐scale brush‐clearing management event, we show how synthetic control can intuitively infer treatment effect sizes from satellite data, even in the presence of confounding noise from climate anomalies, long‐term vegetation dynamics, or sensor errors. We find that accuracy depends on the number and quality of potential control units, highlighting the importance of selecting appropriate control populations. Although we consider the synthetic control approach in the context of natural experiments with remote sensing data, we expect the methodology to have wider utility in ecology, particularly for systems with large, complex, and poorly replicated experimental units.

Ecological Applications↗
USGS2022

Linking evolutionary potential to extinction risk: Applications and future directions

Extinction-risk assessments play a major role in prioritizing conservation action at national and international levels. However, quantifying extinction risk is challenging, especially when including the full suite of adaptive responses to environmental change. In particular, evolutionary potential (EP), the capacity to evolve genetically based changes that increase fitness under changing conditions, has proven difficult to evaluate, limiting its inclusion in risk assessments. Theory, experiments, simulations, and field studies all highlight the importance of EP in characterizing and mitigating extinction risk. Disregarding EP can therefore result in ineffective allocation of resources and inadequate recovery planning. Fortunately, proxies for EP can be estimated from environmental, phenotypic, and genetic data. Some proxies can be incorporated into quantitative extinction-risk assessments, whereas others better inform basic conservation actions that maximize resilience to future change. Integration of EP into conservation decision-making is challenging but essential and remains an important area for innovation in applied conservation science.

Frontiers in Ecology and the Environment↗
USGS2007

Tidal freshwater forested wetlands: Future research needs and an overview of restoration: Chapter 17

Studies of tidal freshwater forested wetlands are few in contrast to the diversity of conditions and information needs that exist for this ecosystem type. Basic information is lacking on the physiological ecology of major wetland tree species under natural settings, the structure and dynamics of pure and mixed species communities, soil-plant interactions, biogeochemistry, hydrology, soils, wildlife habitat, primary biotic and abiotic functions, and the response of these systems to natural and human-caused disruptions. Existing information is often not in a form that can be applied to ecosystem problems, especially those related to management, restoration, or creation of tidal swamps. Accordingly, there is a critical need for research on fundamental biotic and abiotic processes and functions in tidal forested wetland landscapes on a local and regional scale. In this chapter, we detail those research needs, and we highlight some restoration ideas for tidal freshwater forested wetlands with the hope that much additional research will follow.

Book chapter↗
USGS2025

A systematic review and meta-analysis of post-fire seeding and herbicide treatment effectiveness for controlling exotic annual grasses in the sagebrush biome

Introduction Outcomes of ecological restoration treatments can be highly variable and challenging to generalize, even for the same treatment type applied in similar ecological communities at different times and places. Notable examples are the herbicide and seeding treatments that have been extensively applied across the perennial sagebrush steppe of the United States to reduce impacts of fire-promoting exotic annual grasses (EAGs) such as Cheatgrass ( Bromus tectorum ). Objectives We asked if statistically based generalizations about the effects of pre-emergent herbicide and drill seeding of perennials, implemented following wildfires when threats of annual-grass invasion are greatest, could be made from the available literature. Methods We conducted a meta-analysis of these treatment effects for 1228 treatment-control comparisons from 35 studies published from 1990 to 2023 that met basic criteria for topical relevance and repeatability. Results EAGs and forbs were each reduced by herbicides and by seeding perennial grasses. The combination of herbicide and seeding reduced annuals and led to the largest increases in perennials. Although these outcomes support the intended effects of the treatments, there was high variability in outcomes among studies. Conclusions Combined use of pre-emergent herbicides and seeding can increase the success of restoration interventions that are aimed at reducing the invasion of exotic annual grasses and increasing perennials after fire in sagebrush steppe. Our analysis revealed, however, that the available literature was not suited to answering more specific questions, in spite of the massive amount of post-fire herbicide and seedings that have been applied in burned sagebrush steppe. Specifically, there were too few topically relevant studies with adequate scientific reporting to properly evaluate differences among specific treatment methodologies, including specific herbicides, that affect restoration success.

Restoration Ecology↗
USGS2007

Fish movement ecology in high gradient headwater streams: Its relevance to fish passage restoration through stream culvert barriers

Restoration of fish passage through culvert barriers has emerged as a major issue in the Pacific Northwest and nationwide, in part, because of their potential influence on fish movement. Movement is an essential mechanism by which mobile animals acquire the resources necessary for the successful completion of their life-cycles. In this report, we provide a brief review of some essential characteristics of animal movement and examples from a focal group of fishes in Washington State: salmon, trout, and char. We begin by outlining some basic characteristics of animal movement and then apply that foundation to the case of salmonid fishes. Next we consider the consequences of disrupting fish movement with human-constructed barriers, such as culverts. Finally, this body of evidence is summarized, and we propose a short list of what we view as high priority information needs to support more effective restoration of fish passage through culverts.

Open-File Report↗
USGS2010

Trait-based approaches in the analysis of stream fish communities

Species traits are used to study the functional organization of fish communities for a range of reasons, from simply reducing data dimensionality to providing mechanistic explanations for observed variation in communities. Ecological and life history traits have been used to understand the basic ecology of fishes and predict (1) species and community responses to habitat and climate alteration, and (2) species extinction, species invasion, and community homogenization. Many approaches in this arena have been developed during the past three decades, but they often have not been integrated with related ecological concepts or subdisciplines, which has led to confusion in terminology. We review 102 studies of species traits and then summarize patterns in traits being used and questions being addressed with trait-based approaches. Overall, studies of fish–habitat relationships that apply habitat templates and hierarchical filters dominate our sample; the most frequently used traits are related to feeding. We define and show the relationships among key terms such as fundamental and realized niches; functional traits, performance, and fitness; tactic, trait-state, syndromes, and strategies; and guilds and functional groups. We propose accelerating research to (1) quantify trait plasticity, (2) identify traits useful for testing ecological hypotheses, (3) model habitat and biotic interactions in communities while explicitly accounting for phylogenetic relationships, (4) explore how traits control community assembly, and (5) document the importance of traits in fish– community responses to anthropogenic change and in delivering ecosystem services. Further synthesis of these topics is still needed to develop concepts, models, and principles that can unify the disparate approaches taken in trait-based analysis of fish communities, link fish community ecology to general community ecology, and inform sustainable management of ecosystems.

Conference Paper↗