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At least 1,243 records · Page 69Linked to original sources
USGS2015

Determining habitat quality for species that demonstrate dynamic habitat selection

Determining habitat quality for wildlife populations requires relating a species' habitat to its survival and reproduction. Within a season, species occurrence and density can be disconnected from measures of habitat quality when resources are highly seasonal, unpredictable over time, and patchy. Here we establish an explicit link among dynamic selection of changing resources, spatio-temporal species distributions, and fitness for predictive abundance and occurrence models that are used for short-term water management and long-term restoration planning. We used the wading bird distribution and evaluation models (WADEM) that estimate (1) daily changes in selection across resource gradients, (2) landscape abundance of flocks and individuals, (3) conspecific foraging aggregation, and (4) resource unit occurrence (at fixed 400 m cells) to quantify habitat quality and its consequences on reproduction for wetland indicator species. We linked maximum annual numbers of nests detected across the study area and nesting success of Great Egrets (Ardea alba), White Ibises (Eudocimus albus), and Wood Storks (Mycteria americana) over a 20-year period to estimated daily dynamics of food resources produced by WADEM over a 7490 km2 area. For all species, increases in predicted species abundance in March and high abundance in April were strongly linked to breeding responses. Great Egret nesting effort and success were higher when birds also showed greater conspecific foraging aggregation. Synthesis and applications: This study provides the first empirical evidence that dynamic habitat selection processes and distributions of wading birds over environmental gradients are linked with reproductive measures over periods of decades. Further, predictor variables at a variety of temporal (daily-multiannual) resolutions and spatial (400 m to regional) scales effectively explained variation in ecological processes that change habitat quality. The process used here allows managers to develop short- and long-term conservation strategies that (1) consider flexible behavioral patterns and (2) are robust to environmental variation over time.

Florida↗
USGS2022

Environmental DNA methods for ecological monitoring and biodiversity assessment in estuaries

Environmental DNA (eDNA) detection methods can complement traditional biomonitoring to yield new ecological insights in aquatic systems. However, the conceptual and methodological frameworks for aquatic eDNA detection and interpretation were developed primarily in freshwater environments and have not been well established for estuaries and marine environments that are by nature dynamic, turbid, and hydrologically complex. Environmental context and species life history are critical for successful application of eDNA methods, and the challenges associated with eDNA detection in estuaries were the subject of a symposium held at the University of California Davis on January 29, 2020 ( https://marinescience.ucdavis.edu/engagement/past-events/edna ). Here, we elaborate upon topics addressed in the symposium to evaluate eDNA methods in the context of monitoring and biodiversity studies in estuaries. We first provide a concise overview of eDNA science and methods, and then examine the San Francisco Estuary (SFE) as a case study to illustrate how eDNA detection can complement traditional monitoring programs and provide regional guidance on future potential eDNA applications. Additionally, we offer recommendations for enhancing communication between eDNA scientists and natural resource managers, which is essential for integrating eDNA methods into existing monitoring programs. Our intent is to create a resource that is accessible to those outside the field of eDNA, especially managers, without oversimplifying the challenges or advantages of these methods.

Estuaries and Coasts↗
USGS2003

Understanding climatic impacts, vulnerabilities, and adaptation in the United States: Building a capacity for assessment

Based on the experience of the U.S. National Assessment, we propose a program of research and analysis to advance capability for assessment of climate impacts, vulnerabilities, and adaptation options. We identify specific priorities for scientific research on the responses of ecological and socioeconomic systems to climate and other stresses; for improvement in the climatic inputs to impact assessments; and for further development of assessment methods to improve their practical utility to decision-makers. Finally, we propose a new institutional model for assessment, based principally on regional efforts that integrate observations, research, data, applications, and assessment on climate and linked environmental-change issues. The proposed program will require effective collaboration between scientists, resource managers, and other stakeholders, all of whose expertise is needed to define and prioritize key regional issues, characterize relevant uncertainties, and assess potential responses. While both scientifically and organizationally challenging, such an integrated program holds the best promise of advancing our capacity to manage resources and the economy adaptively under a changing climate.

Climatic Change↗
USGS1992

Estimating transition probabilities for stage-based population projection matrices using capture-recapture data

In stage—based demography, animals are often categorized into size (or mass) classes, and size—based probabilities of surviving and changing mass classes must be estimated before demographic analyses can be conducted. In this paper, we develop two procedures for the estimation of mass transition probabilities from capture—recapture data. The first approach uses a multistate capture—recapture model that is parameterized directly with the transition probabilities of interest. Maximum likelihood estimates are then obtained numerically using program SURVIV. The second approach involvesa modification of Pollock's robust design. Estimation proceeds by conditioning on animals caught in a particualr class at time i, and then using closed models to estimate the number of these that are alive in other classes at i + 1. Both methods are illustrated by application to meadow vole, Microtus pennsylvanicus, capture—recapture data. The two methods produced reasonable estimates that were similar. Advantages of these two approaches include the directness of estimation, the absence of need for restrictive assumptions about the independence of survival and growth, the testability of assumptions, and the testability of related hypotheses of ecological interest (e.g., the hypothesis of temporal variation in transition probabilities).

Ecology↗
USGS2018

Synthesis of tree swallow (Tachycineta bicolor) data for Beneficial Use Impairment (BUI) assessment at Wisconsin Areas of Concern

Assessment of the “Bird or Animal Deformities or Reproductive Problems” Beneficial Use Impairment (BUI) can be accomplished by (1) comparing tissue concentrations to established background and Lowest Observable Effect Level (LOEL) for reproductive effects, or (2) directly measuring reproductive success at Areas of Concern (AOCs) and statistically comparing those rates to minimally impacted reference locations (non-AOCs). Results from recent tree swallow ( Tachycineta bicolor) publications were used to evaluate this BUI based on both approaches. For both endpoints, a 95-percent confidence interval (CI) was used to test for significant differences. Additional information on BUIs, AOCs, and the program in general can be found in the Great Lakes Water Quality Agreement (2012). For the first metric, there are good background and reproductive effect threshold LOELs for tree swallow egg concentrations for polychlorinated biphenyls (PCBs), dioxins and furans (PCDD/Fs), and mercury, as well as, for some other organic and inorganic contaminants. For the second assessment, comparisons were made between AOC and non-AOC sites for reproductive success, which was measured as the daily probability of egg failure and the percentage of eggs laid that hatched. Multistate modeling was used to assess whether there was an association between the daily probability of egg failure and a suite of contaminants, including PCBs, but also whether there was an association with ecological variables, such as female age and date within season. Both of these ecological variables are known to affect hatching success in birds. The objective of this report is to synthesize the previously published information to assist in the assessment of the “Bird or Animal Deformities or Reproductive Problems” BUI at 16 sites within the 5 Wisconsin AOCs (table 1). The logic behind this interpretation is applicable to other AOCs as well.

Michigan, Minnesota, Wisconsin↗
USGS2026

Disease-associated mortality drives reduction in Yukon River Chinook salmon escapement: A novel method for quantifying the negative impacts of ‘misfit’ parasites to improve fisheries management

Parasites can suppress host populations through parasite-induced mortality. However, the negative effects of parasites are difficult to measure in wild populations and we have few tools for quantifying the magnitude of parasite-induced mortality. This is especially true for many ‘misfit’ parasites that do not fit into standard classifications (e.g. fungal-like parasites and myxozoans). As such, we are limited in our ability to include the effects of parasites in fish and wildlife management strategies. Chinook salmon ( Oncorhynchus tshawytscha ) are a species of immense cultural and ecological significance but populations are declining across much of their range. In the Yukon River, Alaska, USA, episodic outbreaks of the ichthyosporean parasite Ichthyophonus have been linked to declines, but population-level effects of Ichthyophonus on Yukon Chinook salmon remain largely unknown. We developed a novel model that leverages changes in parasite intensity distributions to quantify the magnitude of disease-induced mortality occurring in host populations. We used it to address two questions to inform management of Yukon Chinook salmon: (i) Is parasite-induced mortality occurring in Chinook salmon and at what magnitude? (ii) What are the drivers of spatio-temporal variability in parasite-induced mortality? Using 3 years of surveys, we quantified the evidence for the presence, magnitude, and variability in Ichthyophonus -induced mortality in Chinook salmon. Our model predicted that Ichthyophonus was responsible for between 8% and 15% mortality of the migrating Chinook salmon population prior to reaching the Canadian border and could describe nearly 35% of unaccounted for mortality at the border. The model predicted that variability in mortality among years could largely be explained by differences in parasite acquisition in the marine environment rather than differences in infection dynamics in the river. Synthesis and applications . Alaska Department of Fish and Game is implementing an annual monitoring program at the mouth of the Yukon River where our model will estimate the proportion of fish at risk from parasite-induced mortality to inform annual management. Moreover, the model is broadly applicable to other fungal-like and myxozoan parasites of conservation concern, where improved estimates of parasite-induced mortality could be used to predict parasite suppression of wild and managed host populations.

Alaska↗
USGS2009

Defining fish nursery habitats: An application of otolith elemental fingerprinting in Tampa Bay, Florida

Fishing in Tampa Bay enhances the quality of life of the area's residents and visitors. However, people's desire to settle along the Bay's shorelines and tributaries has been detrimental to the very habitat believed to be crucial to prime target fishery species. Common snook (Centropomus undecimalis) and red drum (Sciaenops ocellatus) are part of the suite of estuarine fishes that 1) are economically or ecologically prominent, and 2) have complex life cycles involving movement between open coastal waters and estuarine nursery habitats, including nursery habitats that are located within upstream, low-salinity portions of the Bay?s tidal tributaries. We are using an emerging microchemical technique -- elemental fingerprinting of fish otoliths -- to determine the degree to which specific estuarine locations contribute to adult fished populations in Tampa Bay. In ongoing monitoring surveys, over 1,000 young-of-the-year common snook and red drum have already been collected from selected Tampa Bay tributaries. Using laser ablation-inductively coupled plasma - mass spectrometry (LA-ICP-MS), we are currently processing a subsample of these archived otoliths to identify location-specific fingerprints based on elemental microchemistry. We will then analyze older fish from the local fishery in order to match them to their probable nursery areas, as defined by young-of-the-year otoliths. We expect to find that some particularly favorable nursery locations contribute disproportionately to the fished population. In contrast, other nursery areas may be degraded, or act as 'sinks', thereby decreasing their contribution to the fish population. Habitat managers can direct strategic efforts to protect any nursery locations that are found to be of prime importance in contributing to adult stocks.

Florida↗
USGS2016

Uncertainty in biological monitoring: a framework for data collection and analysis to account for multiple sources of sampling bias

Biological monitoring programmes are increasingly relying upon large volumes of citizen-science data to improve the scope and spatial coverage of information, challenging the scientific community to develop design and model-based approaches to improve inference. Recent statistical models in ecology have been developed to accommodate false-negative errors, although current work points to false-positive errors as equally important sources of bias. This is of particular concern for the success of any monitoring programme given that rates as small as 3% could lead to the overestimation of the occurrence of rare events by as much as 50%, and even small false-positive rates can severely bias estimates of occurrence dynamics. We present an integrated, computationally efficient Bayesian hierarchical model to correct for false-positive and false-negative errors in detection/non-detection data. Our model combines independent, auxiliary data sources with field observations to improve the estimation of false-positive rates, when a subset of field observations cannot be validated a posteriori or assumed as perfect. We evaluated the performance of the model across a range of occurrence rates, false-positive and false-negative errors, and quantity of auxiliary data. The model performed well under all simulated scenarios, and we were able to identify critical auxiliary data characteristics which resulted in improved inference. We applied our false-positive model to a large-scale, citizen-science monitoring programme for anurans in the north-eastern United States, using auxiliary data from an experiment designed to estimate false-positive error rates. Not correcting for false-positive rates resulted in biased estimates of occupancy in 4 of the 10 anuran species we analysed, leading to an overestimation of the average number of occupied survey routes by as much as 70%. The framework we present for data collection and analysis is able to efficiently provide reliable inference for occurrence patterns using data from a citizen-science monitoring programme. However, our approach is applicable to data generated by any type of research and monitoring programme, independent of skill level or scale, when effort is placed on obtaining auxiliary information on false-positive rates.

Methods in Ecology and Evolution↗
USGS2017

Enhancing the interpretation of stated choice analysis through the application of a verbal protocol assessment

A stated choice survey was employed to evaluate the relative importance of resource, social, and management attributes by asking visitors to select preferred configurations of these attributes. A verbal protocol assessment was added to consider how respondents interpret and respond to stated choice questions applied to hikers of a popular trail at Acadia National Park. Results suggest that visitors are sensitive to changes in public access to the trail and its ecological conditions, with level of encounters least important. Verbal protocol results identified considerations made by respondents that provide insight to their evaluations of alternative recreation setting configurations. These insights help clarify issues important to visitors that stated choice results on their own do not provide.

Maine↗
USGS2015

Ecosystem services science, practice, and policy: Perspectives from ACES, A Community on Ecosystem Services

Ecosystem services are at a crossroad. The natural capital needed to produce them is diminishing (Millennium Ecosystem Assessment, 2005). At the same time, the science relating to their identification, production, and valuation is advancing. Examples of ecosystem services applications are abundant in the literature. In addition, the concept of ecosystem services and its applications are attracting attention and are becoming more visible. The concept of ecosystem services, however, is still not routinely applied to many natural resource management decisions.

Ecological Economics↗
USGS2017

Density-dependent vulnerability of forest ecosystems to drought

1. Climate models predict increasing drought intensity and frequency for many regions, which may have negative consequences for tree recruitment, growth and mortality, as well as forest ecosystem services. Furthermore, practical strategies for minimizing vulnerability to drought are limited. Tree population density, a metric of tree abundance in a given area, is a primary driver of competitive intensity among trees, which influences tree growth and mortality. Manipulating tree population density may be a mechanism for moderating drought-induced stress and growth reductions, although the relationship between tree population density and tree drought vulnerability remains poorly quantified, especially across climatic gradients. 2. In this study, we examined three long-term forest ecosystem experiments in two widely distributed North American pine species, ponderosa pine Pinus ponderosa (Lawson & C. Lawson) and red pine Pinus resinosa (Aiton), to better elucidate the relationship between tree population density, growth and drought. These experiments span a broad latitude and aridity range and include tree population density treatments that have been purposefully maintained for several decades. We investigated how tree population density influenced resistance (growth during drought) and resilience (growth after drought compared to pre-drought growth) of stand-level growth during and after documented drought events. 3. Our results show that relative tree population density was negatively related to drought resistance and resilience, indicating that trees growing at lower densities were less vulnerable to drought. This result was apparent in all three forest ecosystems, and was consistent across species, stand age and drought intensity. 4. Synthesis and applications . Our results highlighted that managing pine forest ecosystems at low tree population density represents a promising adaptive strategy for reducing the adverse impacts of drought on forest growth in coming decades. Nonetheless, the broader applicability of our findings to other types of forest ecosystems merits additional investigation.

Journal of Applied Ecology↗
USGS2016

Detection limits of quantitative and digital PCR assays and their influence in presence-absence surveys of environmental DNA

A set of universal guidelines is needed to determine the limit of detection (LOD) in PCR-based analyses of low concentration DNA. In particular, environmental DNA (eDNA) studies require sensitive and reliable methods to detect rare and cryptic species through shed genetic material in environmental samples. Current strategies for assessing detection limits of eDNA are either too stringent or subjective, possibly resulting in biased estimates of species’ presence. Here, a conservative LOD analysis grounded in analytical chemistry is proposed to correct for overestimated DNA concentrations predominantly caused by the concentration plateau, a nonlinear relationship between expected and measured DNA concentrations. We have used statistical criteria to establish formal mathematical models for both quantitative and droplet digital PCR. To assess the method, a new Grass Carp ( Ctenopharyngodon idella ) TaqMan assay was developed and tested on both PCR platforms using eDNA in water samples. The LOD adjustment reduced Grass Carp occupancy and detection estimates while increasing uncertainty – indicating that caution needs to be applied to eDNA data without LOD correction. Compared to quantitative PCR, digital PCR had higher occurrence estimates due to increased sensitivity and dilution of inhibitors at low concentrations. Without accurate LOD correction, species occurrence and detection probabilities based on eDNA estimates are prone to a source of bias that cannot be reduced by an increase in sample size or PCR replicates. Other applications also could benefit from a standardized LOD such as GMO food analysis, and forensic and clinical diagnostics.

Molecular Ecology Resources↗
USGS2012

Ecosystem services from keystone species: diversionary seeding and seed-caching desert rodents can enhance Indian ricegrass seedling establishment

Seeds of Indian ricegrass (Achnatherum hymenoides), a native bunchgrass common to sandy soils on arid western rangelands, are naturally dispersed by seed-caching rodent species, particularly Dipodomys spp. (kangaroo rats). These animals cache large quantities of seeds when mature seeds are available on or beneath plants and recover most of their caches for consumption during the remainder of the year. Unrecovered seeds in caches account for the vast majority of Indian ricegrass seedling recruitment. We applied three different densities of white millet (Panicum miliaceum) seeds as “diversionary foods” to plots at three Great Basin study sites in an attempt to reduce rodents' over-winter cache recovery so that more Indian ricegrass seeds would remain in soil seedbanks and potentially establish new seedlings. One year after diversionary seed application, a moderate level of Indian ricegrass seedling recruitment occurred at two of our study sites in western Nevada, although there was no recruitment at the third site in eastern California. At both Nevada sites, the number of Indian ricegrass seedlings sampled along transects was significantly greater on all plots treated with diversionary seeds than on non-seeded control plots. However, the density of diversionary seeds applied to plots had a marginally non-significant effect on seedling recruitment, and it was not correlated with recruitment patterns among plots. Results suggest that application of a diversionary seed type that is preferred by seed-caching rodents provides a promising passive restoration strategy for target plant species that are dispersed by these rodents.

California;Nevada↗
USGS1984

Reproduction by an altricial songbird, the red-winged blackbird, in fields treated with the organophosphate insecticide fenthion

(1) Breeding red-winged blackbirds were used as a model to study the effects of a single application of an organophosphate insecticide, fenthion, on reproduction of altricial songbirds. (2) The insecticide had no significant effect on frequency of nest abandonment, clutch size, hatching success, or fledgling success. (3) Growth rates of young nestlings were lower in nests on one of two treated areas, but overall growth rates of survivors were not significantly different from controls in nests on nearby unsprayed areas. (4) The insecticide had no measured effect on male spatial organization. (5) Measures of abundance of the principal nestling food item, noctuid larvae, showed that one application of the insecticide significantly reduced the abundance of the food supply, but the reduction of food supply did not result in a decrease in nestling growth rates or fledgling success.

Wyoming↗
USGS2019

Recovery planning in a dynamic system: Integrating uncertainty into a decision support tool for an endangered songbird

Along the Santa Clara River in California, populations of the federally and state-listed Least Bell's Vireo ( Vireo bellii pusillus ) are recovering from near extirpation. Habitat protection and restoration, as well as controlling rates of brood parasitism, are thought to be the primary drivers of this recovery. Continuing successful management of this population faces multiple challenges due to the highly dynamic and unpredictable nature of the system, lack of clearly defined and measurable recovery criteria, parametric and stochastic uncertainty, and data limitations. Many of these management challenges are not unique to Least Bell's Vireo and require careful balancing of limited resources into the future. We developed a decision support tool as a user interface for exploring the underlying uncertainty in a population viability analysis under an array of different management scenarios. The tool was designed to assist with the planning and coordination between conservation partners in the region in three distinct aspects of the decision-making process: defining the problem and setting clear goals and objectives, exploring the consequences of potential alternative actions, and identifying criteria for ongoing evaluation and monitoring. The general framework for the design of this decision support tool is broadly applicable to many management and decision-making scenarios that share these common challenges.

California↗
USGS2013

A hierarchical nest survival model integrating incomplete temporally varying covariates

Nest success is a critical determinant of the dynamics of avian populations, and nest survival modeling has played a key role in advancing avian ecology and management. Beginning with the development of daily nest survival models, and proceeding through subsequent extensions, the capacity for modeling the effects of hypothesized factors on nest survival has expanded greatly. We extend nest survival models further by introducing an approach to deal with incompletely observed, temporally varying covariates using a hierarchical model. Hierarchical modeling offers a way to separate process and observational components of demographic models to obtain estimates of the parameters of primary interest, and to evaluate structural effects of ecological and management interest. We built a hierarchical model for daily nest survival to analyze nest data from reintroduced whooping cranes (Grus americana) in the Eastern Migratory Population. This reintroduction effort has been beset by poor reproduction, apparently due primarily to nest abandonment by breeding birds. We used the model to assess support for the hypothesis that nest abandonment is caused by harassment from biting insects. We obtained indices of blood-feeding insect populations based on the spatially interpolated counts of insects captured in carbon dioxide traps. However, insect trapping was not conducted daily, and so we had incomplete information on a temporally variable covariate of interest. We therefore supplemented our nest survival model with a parallel model for estimating the values of the missing insect covariates. We used Bayesian model selection to identify the best predictors of daily nest survival. Our results suggest that the black fly Simulium annulus may be negatively affecting nest survival of reintroduced whooping cranes, with decreasing nest survival as abundance of S. annulus increases. The modeling framework we have developed will be applied in the future to a larger data set to evaluate the biting-insect hypothesis and other hypotheses for nesting failure in this reintroduced population; resulting inferences will support ongoing efforts to manage this population via an adaptive management approach. Wider application of our approach offers promise for modeling the effects of other temporally varying, but imperfectly observed covariates on nest survival, including the possibility of modeling temporally varying covariates collected from incubating adults.

Wisconsin↗
USGS2017

Advancing mangrove macroecology

Mangrove forests provide a wide range of ecosystem services to society, yet they are among the most anthropogenically impacted coastal ecosystems in the world. In this chapter, we discuss and provide examples for how macroecology can advance our understanding of mangrove ecosystems. Macroecology is broadly defined as a discipline that uses statistical analyses to investigate large-scale, universal patterns in the distribution, abundance, diversity, and organization of species and ecosystems, including the scaling of ecological processes and structural and functional relationships. Macroecological methods can be used to advance our understanding of how non-linear responses in natural systems can be triggered by human impacts at local, regional, and global scales. Although macroecology has the potential to gain knowledge on universal patterns and processes that govern mangrove ecosystems, the application of macroecological methods to mangroves has historically been limited by constraints in data quality and availability. Here we provide examples that include evaluations of the variation in mangrove forest ecosystem structure and function in relation to macroclimatic drivers (e.g., temperature and rainfall regimes) and climate change. Additional examples include work focused upon the continental distribution of aboveground net primary productivity and carbon storage, which are rapidly advancing research areas. These examples demonstrate the value of a macroecological perspective for the understanding of global- and regional-scale effects of both changing environmental conditions and management actions on ecosystem structure, function, and the supply of goods and services. We also present current trends in mangrove modeling approaches and their potential utility to test hypotheses about mangrove structural and functional properties. Given the gap in relevant experimental work at the regional scale, we also discuss the potential use of mangrove restoration and rehabilitation projects as macroecological studies that advance the critical selection and conservation of ecosystem services when managing mangrove resources. Future work to further incorporate macroecology into mangrove research will require a concerted effort by research groups and institutions to launch research initiatives and synthesize data collected across broad biogeographic regions.

Book chapter↗
USGS2009

LANDFIRE: A nationally consistent vegetation, wildland fire, and fuel assessment

LANDFIRE is a 5-year, multipartner project producing consistent and comprehensive maps and data describing vegetation, wildland fuel, fire regimes and ecological departure from historical conditions across the United States. It is a shared project between the wildland fire management and research and development programs of the US Department of Agriculture Forest Service and US Department of the Interior. LANDFIRE meets agency and partner needs for comprehensive, integrated data to support landscape-level fire management planning and prioritization, community and firefighter protection, effective resource allocation, and collaboration between agencies and the public. The LANDFIRE data production framework is interdisciplinary, science-based and fully repeatable, and integrates many geospatial technologies including biophysical gradient analyses, remote sensing, vegetation modelling, ecological simulation, and landscape disturbance and successional modelling. LANDFIRE data products are created as 30-m raster grids and are available over the internet at www.landfire.gov , accessed 22 April 2009. The data products are produced at scales that may be useful for prioritizing and planning individual hazardous fuel reduction and ecosystem restoration projects; however, the applicability of data products varies by location and specific use, and products may need to be adjusted by local users.

International Journal of Wildland Fire↗