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At least 253 records · Page 14Linked to original sources
USGS2015

Soil ecology of a rock outcrop ecosystem: Abiotic stresses, soil respiration, and microbial community profiles in limestone cedar glades

Limestone cedar glades are a type of rock outcrop ecosystem characterized by shallow soil and extreme hydrologic conditions—seasonally ranging from xeric to saturated—that support a number of plant species of conservation concern. Although a rich botanical literature exists on cedar glades, soil biochemical processes and the ecology of soil microbial communities in limestone cedar glades have largely been ignored. This investigation documents the abiotic stress regime of this ecosystem (shallow soil, extreme hydrologic fluctuations and seasonally high soil surface temperatures) as well as soil physical and chemical characteristics, and relates both types of information to ecological structures and functions including vegetation, soil respiration, and soil microbial community metabolic profiles and diversity. Methods used in this investigation include field observations and measurements of soil physical and chemical properties and processes, laboratory analyses, and microbiological assays of soil samples. Stress factors quantified by this research include shallow soil (depth to bedrock ranging from 2.4 to 22.6 cm), volumetric soil water content levels seasonally ranging from xeric (below 5%) to saturated (above 50%), and seasonally extreme ground-surface temperatures (above 48°C). Findings from this research indicate that spatial and temporal heterogeneity exists in limestone cedar glades in terms of abiotic stress factors and soil physical and chemical properties. Several such soil properties (e.g. soil depth, organic matter levels, pH, and particle size distribution) are spatially correlated. These soil properties were statistically related to ecological structures and functions such as vegetation patterns, soil respiration, the density of culturable heterotrophic microbes in soil and metabolic diversity of soil microbial community profiles. In general, zones within limestone cedar glades that had relatively shallow soil, alkaline pH, low levels of organic matter and high levels of silt also tended to have depressed rates of soil respiration and reduced densities and metabolic diversity of culturable heterotrophic soil microbes. Additionally, seasonally-relevant stress factors including soil water content and temperatures at or near the soil surface were related to the same set of ecological structures and functions.

Tennessee↗
USGS2010

Avalanche ecology and large magnitude avalanche events: Glacier National Park, Montana, USA

Large magnitude snow avalanches play an important role ecologically in terms of wildlife habitat, vegetation diversity, and sediment transport within a watershed. Ecological effects from these infrequent avalanches can last for decades. Understanding the frequency of such large magnitude avalanches is also critical to avalanche forecasting for the Going-to-the-Sun Road (GTSR). In January 2009, a large magnitude avalanche cycle occurred in and around Glacier National Park, Montana. The study site is the Little Granite avalanche path located along the GTSR. The study is designed to quantify change in vegetative cover immediately after a large magnitude event and document ecological response over a multi-year period. GPS field mapping was completed to determine the redefined perimeter of the avalanche path. Vegetation was inventoried using modified U.S. Forest Service Forest Inventory and Analysis plots, cross sections were taken from over 100 dead trees throughout the avalanche path, and an avalanche chronology was developed. Initial results indicate that the perimeter of this path was expanded by 30%. The avalanche travelled approximately 1200 vertical meters and 3 linear kilometers. Stands of large conifers as old as 150 years were decimated by the avalanche, causing a shift in dominant vegetation types in many parts of the avalanche path. Woody debris is a major ground cover up to 3 m in depth on lower portions of the avalanche path and will likely affect tree regrowth. Monitoring and measuring the post-avalanche vegetation recovery of this particular avalanche path provides a unique dataset for determining the ecological role of avalanches in mountain landscapes.

Montana↗
USGS2014

A new map of global ecological land units — An ecophysiographic stratification approach

In response to the need and an intergovernmental commission for a high resolution and data-derived global ecosystem map, land surface elements of global ecological pattern were characterized in an ecophysiographic stratification of the planet. The stratification produced 3,923 terrestrial ecological land units (ELUs) at a base resolution of 250 meters. The ELUs were derived from data on land surface features in a three step approach. The first step involved acquiring or developing four global raster datalayers representing the primary components of ecosystem structure: bioclimate, landform, lithology, and land cover. These datasets generally represent the most accurate, current, globally comprehensive, and finest spatial and thematic resolution data available for each of the four inputs. The second step involved a spatial combination of the four inputs into a single, new integrated raster dataset where every cell represents a combination of values from the bioclimate, landforms, lithology, and land cover datalayers. This foundational global raster datalayer, called ecological facets (EFs), contains 47,650 unique combinations of the four inputs. The third step involved an aggregation of the EFs into the 3,923 ELUs. This subdivision of the Earth’s surface into relatively fine, ecological land areas is designed to be useful for various types of ecosystem research and management applications, including assessments of climate change impacts to ecosystems, economic and non-economic valuation of ecosystem services, and conservation planning.

Book↗
USGS2020

Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System

Smallmouth buffalo (Ictiobus bubalus) is a common and widely distributed large-bodied species of the family Catostomidae. It inhabits large rivers and reservoirs of the eastern continental United States (east of the continental Divide) and is most abundant and common in the large rivers of the Midwest and Central Plains, though it does occur as far north and east as the Hudson Bay drainage and as far south and west as Arizona (Edwards and Twoney 1982). Historically, smallmouth buffalo were an important component of commercial fisheries on both the Mississippi and Illinois Rivers. However, following the introduction of common carp (Cyprinus carpio) in the mid-1800s (Carlander 1954), the construction of a system of navigation dams on Upper Mississippi and Illinois River in the 1930s (USGS 1999), and water quality/pollution issues through the 1980s (Weiner 2010), the role of smallmouth buffalo in the overall UMRS fish community and commercial fishery has generally diminished relative to historical standards. Still, smallmouth buffalo remains an important and valued component of the UMRS commercial fishery. The study area is represented by three study reaches on the Illinois River and three study reaches on the Upper Mississippi River (Figure 1). Collectively, these study reaches represent nearly 1200 river km and exist across strong and pronounced ecological and disturbance gradients. For example, habitat composition, water quality, commercial navigation intensity, aquatic plant prominence, and the number and abundance of nonnative fish species vary strongly across the study domain, with northern Mississippi River reaches exhibiting less navigation traffic, better water quality, markedly greater aquatic plant prominence, more diverse habitat composition, and comparably much smaller numbers of nonnative species than the lower Mississippi River study reach and those on the Illinois River (USGS 1999; Johnson and Hagerty [eds] 2008; Irons et al. 2009). Long term monitoring efforts conducted under the auspices of the Upper Mississippi River Restoration program over the past 27 years have provided tremendous insights into shifts and changes of the overall UMRS fish community (Ickes et al. 2005; Garvey et al. 2010; Schramm and Ickes 2016). However, these monitoring efforts observe only the most basic aspects of the UMRS fish community (i.e., catch, length, weight, distribution, and occurrence). To gain a greater understanding of forces driving community level shifts and changes, more directed study is needed on the functional attributes of fish populations (i.e., growth, mortality, recruitment). Collectively, these functional attributes of populations are termed population dynamics and/or vital rates. It is important to note, the population dynamics of fishes in large rivers is generally poorly understood, especially for non-game species (Ickes 2018). The prevailing view is that abiotic factors largely govern inter-annual population dynamics, typically based upon rather short-term observations and correlations with assorted abiotic river attributes that vary on a seasonal or annual basis (for example, Risotto and Turner 1985). However, the role that longer-term abiotic factors play in regulating population abundance, or that biotic factors internal to the population (e.g., spawner-recruit dynamics, growth dynamics) or external to the population (e.g., predator-prey dynamics, sympatric competitors, disease) remain poorly understood. Achieving a greater understanding of these dynamics is important for stock, game, and invasive species management. In 2017, as part of a larger study designed to gain vital population rate information for smallmouth buffalo in the Upper Mississippi and Illinois Rivers (“Smallmouth Buffalo population demographics of the Upper Mississippi River System”; UMRR LTRM 2018SOW project items 2018MMBF1-2018MMBF6) annual growth patterns in smallmouth buffalo were determined and evaluated. This was accomplished by measuring growth histories recorded in annual growth increments on hard bony parts (here otoliths), a method known generically as biochronology, and somewhat analogous to dendrochronology practiced by foresters. These methods allow one to generate time-series of annual growth histories that depend upon age, year class (i.e., cohort), and annual environmental conditions experienced by the population over time (Weisberg, 1993). Biochronology methods were used to develop a 36-year time series of smallmouth buffalo growth in the Upper Mississippi and Illinois Rivers across a 1200 km ecological and human use disturbance gradient. Annual growth intervals were identified and measured from otoliths to determine fish age and growth history. A mixed model that parses the growth increment into age and year effects was fit to these data. Given the pronounced ecological and disturbance gradients inherent to the UMRS and the study domain, an a priori expectation of differing patterns in growth is accepted as a null hypothesis to test. The goal of this study was to model smallmouth buffalo growth as a function of the age of the fish and the growth year in which the growth was gained. The primary modeling objective was to parse growth observed on each annulus into a portion attributable to the age of the fish and the portion attributable to the year in which the growth was gained. In effect, this modeling approach removes the somewhat trivial age effects on growth so that a non-confounded growth year effect can be gained. Results attributable to growth year provide a time series of growth information that is of the same duration as the oldest fish observed and solely reflects environmental influences on growth. These model responses can then be investigated relative to environmental covariate time-series suspected of influencing growth of smallmouth buffalo in the Upper Mississippi and Illinois Rivers (e.g., temperature, discharge, population density, population mortality, forage availability, sympatric competition, habitat composition, navigation intensity, nonnative fish prominence, etc.). Thus, the primary scientific objective was to investigate if and how smallmouth buffalo growth varies in accordance with innate ecological and disturbance gradients across the study domain.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2021

Temporal invariance of social-ecological catchments

Natural resources such as waterbodies, public parks, and wildlife refuges attract people from varying distances on the landscape, creating "social-ecological catchments." Catchments have provided great utility for understanding physical and social relationships within specific disciplines. Yet, catchments are rarely used across disciplines, such as its application to understand complex spatiotemporal dynamics between mobile human users and patchily distributed natural resources. We collected residence ZIP codes from 19,983 angler parties during 2014–2017 to construct seven angler–waterbody catchments in Nebraska, USA. We predicted that sizes of dense (10% utilization distribution) and dispersed (95% utilization distribution) angler–waterbody catchments would change across seasons and years as a function of diverse resource selection among mobile anglers. Contrary to expectations, we revealed that catchment size was invariant. We discuss how social (conservation actions) and ecological (low water quality, reduction in species diversity) conditions are expected to impact landscape patterns in resource use. We highlight how this simple concept and user-friendly technique can inform timely landscape-level conservation decisions within coupled social-ecological systems that are currently difficult to study and understand.

Ecological Applications↗
USGS2021

Advancing estuarine ecological forecasts: Seasonal hypoxia in Chesapeake Bay

Ecological forecasts are quantitative tools that can guide ecosystem management. The coemergence of extensive environmental monitoring and quantitative frameworks allows for widespread development and continued improvement of ecological forecasting systems. We use a relatively simple estuarine hypoxia model to demonstrate advances in addressing some of the most critical challenges and opportunities of contemporary ecological forecasting, including predictive accuracy, uncertainty characterization, and management relevance. We explore the impacts of different combinations of forecast metrics, drivers, and driver time windows on predictive performance. We also incorporate multiple sets of state-variable observations from different sources and separately quantify model prediction error and measurement uncertainty through a flexible Bayesian hierarchical framework. Results illustrate the benefits of (1) adopting forecast metrics and drivers that strike an optimal balance between predictability and relevance to management, (2) incorporating multiple data sources in the calibration data set to separate and propagate different sources of uncertainty, and (3) using the model in scenario mode to probabilistically evaluate the effects of alternative management decisions on future ecosystem state. In the Chesapeake Bay, the subject of this case study, we find that average summer or total annual hypoxia metrics are more predictable than monthly metrics and that measurement error represents an important source of uncertainty. Application of the model in scenario mode suggests that absent watershed management actions over the past decades, long-term average hypoxia would have increased by 7% compared to 1985. Conversely, the model projects that if management goals currently in place to restore the Bay are met, long-term average hypoxia would eventually decrease by 32% with respect to the mid-1980s.

Chesapeake Bay↗
USGS2017

Ad hoc instrumentation methods in ecological studies produce highly biased temperature measurements

In light of global climate change, ecological studies increasingly address effects of temperature on organisms and ecosystems. To measure air temperature at biologically relevant scales in the field, ecologists often use small, portable temperature sensors. Sensors must be shielded from solar radiation to provide accurate temperature measurements, but our review of 18 years of ecological literature indicates that shielding practices vary across studies (when reported at all), and that ecologists often invent and construct ad hoc radiation shields without testing their efficacy. We performed two field experiments to examine the accuracy of temperature observations from three commonly used portable data loggers (HOBO Pro, HOBO Pendant, and iButton hygrochron) housed in manufactured Gill shields or ad hoc, custom‐fabricated shields constructed from everyday materials such as plastic cups. We installed this sensor array (five replicates of 11 sensor‐shield combinations) at weather stations located in open and forested sites. HOBO Pro sensors with Gill shields were the most accurate devices, with a mean absolute error of 0.2°C relative to weather stations at each site. Error in ad hoc shield treatments ranged from 0.8 to 3.0°C, with the largest errors at the open site. We then deployed one replicate of each sensor‐shield combination at five sites that varied in the amount of urban impervious surface cover, which presents a further shielding challenge. Bias in sensors paired with ad hoc shields increased by up to 0.7°C for every 10% increase in impervious surface. Our results indicate that, due to variable shielding practices, the ecological literature likely includes highly biased temperature data that cannot be compared directly across studies. If left unaddressed, these errors will hinder efforts to predict biological responses to climate change. We call for greater standardization in how temperature data are recorded in the field, handled in analyses, and reported in publications.

Ecology and Evolution↗
USGS2019

Accumulating evidence in ecology: Once is not enough

Many published studies in ecological science are viewed as stand-alone investigations that purport to provide new insights into how ecological systems behave based on single analyses. But it is rare for results of single studies to provide definitive results, as evidenced in current discussions of the “reproducibility crisis” in science. The key step in science is the comparison of hypothesis-based predictions with observations, where the predictions are typically generated by hypothesis-specific models. Repeating this step allows us to gain confidence in the predictive ability of a model, and its corresponding hypothesis, and thus to accumulate evidence and eventually knowledge. This accumulation may occur via an ad hoc approach, via meta-analyses, or via a more systematic approach based on the anticipated evolution of an information state. We argue the merits of this latter approach, provide an example, and discuss implications for designing sequences of studies focused on a particular question. We conclude by discussing current data collection programs that are pre-adapted to use this approach and argue that expanded use would increase the rate of learning in ecology, as well as our confidence in what is learned.

Ecology and Evolution↗
USGS2025

The breeding season and movement ecology of male white‐tailed deer in southwest Wisconsin

White-tailed deer ( Odocoileus virginianus ; hereafter, deer) have been widely studied regarding their breeding ecology and responses to hunting pressures. However, variations in defining the breeding season—its duration and timing—across studies have created uncertainty about whether regional differences in deer breeding ecology stem from ecological factors or methodological inconsistencies. This study aims to clarify the peak breeding season timing and the movement patterns of males during this period, particularly in relation to hunting seasons. Understanding how age and the timing of hunting seasons impact movement and breeding behaviors is important for wildlife managers, as these factors can affect harvest success. This study took place in southwest Wisconsin, using GPS data collected from 188 collared male deer between 15 October and 1 December from 2017 to 2020. Based on generalized linear mixed models, 2-year-old males exhibited higher hourly movement rates than other ages, and the opening weekend of the firearm hunting season had no significant effect on movement rates. In contrast, the variance in daily movement rate differed significantly between yearlings and older ages, with males 3 years and older displaying the highest variance. This suggests that older males may alternate more frequently between high-movement mate searching and lower-movement mate tending, potentially enhancing reproductive success. Similarly, 2-year-old males had larger daily ranges than both older and younger ages. Changepoint analysis of daily movement rates determined that the peak breeding season occurred between 23 October and 12 November, with little variation among ages and alternative metrics. Our findings indicate that male movement rates and ranges can reflect deer reproductive efforts and vary by age, which has important implications for reproductive success and disease transmission risk.

Wisconsin↗
USGS2016

Changing disturbance regimes, ecological memory, and forest resilience

Ecological memory is central to how ecosystems respond to disturbance and is maintained by two types of legacies – information and material. Species life-history traits represent an adaptive response to disturbance and are an information legacy; in contrast, the abiotic and biotic structures (such as seeds or nutrients) produced by single disturbance events are material legacies. Disturbance characteristics that support or maintain these legacies enhance ecological resilience and maintain a “safe operating space” for ecosystem recovery. However, legacies can be lost or diminished as disturbance regimes and environmental conditions change, generating a “resilience debt” that manifests only after the system is disturbed. Strong effects of ecological memory on post-disturbance dynamics imply that contingencies (effects that cannot be predicted with certainty) of individual disturbances, interactions among disturbances, and climate variability combine to affect ecosystem resilience. We illustrate these concepts and introduce a novel ecosystem resilience framework with examples of forest disturbances, primarily from North America. Identifying legacies that support resilience in a particular ecosystem can help scientists and resource managers anticipate when disturbances may trigger abrupt shifts in forest ecosystems, and when forests are likely to be resilient.

Frontiers in Ecology and the Environment↗
USGS2023

Compact or sprawling cities: Has the sparing-sharing framework yielded an ecological verdict?

Purpose of Review Global urban land area is growing faster than the urban population, raising concerns that sprawling, low-density development will reduce biodiversity and human wellbeing. The sparing-sharing framework, adapted from agroecology, provides one approach to assessing alternative urban growth patterns. It compares ecological outcomes in landscapes matched for total population and land area, but differing in configuration: land sparing (partitioned between densely urbanized and undeveloped areas) or land sharing (low-density development throughout). We reviewed the urban sparing-sharing literature since 2010 and recovered 15 studies conducted in 22 cities on four continents. Recent Findings Collectively, studies assessed effects of alternative development patterns on 296 species, 21 community metrics (such as species richness), and 26 indicators of ecosystem services or processes (such as carbon sequestration). Sparing was the best option for 51% of individual species; 43% of community metrics; and 27% of ecosystem service indicators. Summary Existing ecological research does not clearly favor one pattern or the other, and new approaches are needed to facilitate decision making and ecological insight. Specifically, future work could (1) explicitly evaluate optimized urban development patterns across multiple competing priorities (such as providing housing, delivering ecosystem services, and protecting priority species), (2) tackle issues of spatial scale and connectivity that are often ambiguous in sparing-sharing research, and (3) improve geographical representation. These advances can be made while preserving the key insight of the framework–that choices between alternative landscape configurations are only meaningful when those landscapes are matched for total area and the level of human needs met.

Current Landscape Ecology Reports↗
USGS2008

Ecological community integration increases with added trophic complexity

The existence of functional biological organization at the level of multi-species communities has long been contested in ecology and evolutionary biology. I found that adding a trophic level to simulated ecological communities enhanced their ability to compete at the community level, increasing the likelihood of one community forcing all or most species in a second community to extinction. Community-level identity emerged within systems of interacting ecological networks, while competitive ability at the community level was enhanced by intense within-community selection pressure. These results suggest a reassessment of the nature of biological organization above the level of species, indicating that the drive toward biological integration, so prominent throughout the history of life, might extend to multi-species communities.

Ecological Complexity↗
USGS2017

The practice of prediction: What can ecologists learn from applied, ecology-related fields?

The pervasive influence of human induced global environmental change affects biodiversity across the globe, and there is great uncertainty as to how the biosphere will react on short and longer time scales. To adapt to what the future holds and to manage the impacts of global change, scientists need to predict the expected effects with some confidence and communicate these predictions to policy makers. However, recent reviews found that we currently lack a clear understanding of how predictable ecology is, with views seeing it as mostly unpredictable to potentially predictable, at least over short time frames. However, in applied, ecology-related fields predictions are more commonly formulated and reported, as well as evaluated in hindsight, potentially allowing one to define baselines of predictive proficiency in these fields. We searched the literature for representative case studies in these fields and collected information about modeling approaches, target variables of prediction, predictive proficiency achieved, as well as the availability of data to parameterize predictive models. We find that some fields such as epidemiology achieve high predictive proficiency, but even in the more predictive fields proficiency is evaluated in different ways. Both phenomenological and mechanistic approaches are used in most fields, but differences are often small, with no clear superiority of one approach over the other. Data availability is limiting in most fields, with long-term studies being rare and detailed data for parameterizing mechanistic models being in short supply. We suggest that ecologists adopt a more rigorous approach to report and assess predictive proficiency, and embrace the challenges of real world decision making to strengthen the practice of prediction in ecology.

Ecological Complexity↗
USGS2026

A Bayesian hierarchical modeling approach for species diversity in ecology

Species diversity is the foundation of many ecological disciplines. This metric is often approximated using species richness and evenness, even though actual richness likely exceeds observations due to imperfect sampling methods. Estimating the “true” species richness, which includes identifying the number of missing species, has intrigued ecologists for decades. We adopted a parametric model that appeared in Fisher et al. (1943), which models the numbers of individuals from different species as random samples from a negative binomial distribution, and developed a Bayesian computational approach to directly estimate the distribution model parameters. The model parameters represent species abundance and evenness, and can be used to derive species richness. We evaluated our parametric approach using (1) a simulation study and (2) three historical data sets. Furthermore, we illustrated the hierarchical modeling approach to combine data from multiple parallel studies using a biannual fishery survey data set. Our parametric model formulation is computationally efficient, and the hierarchical structure facilitates embedding diversity estimation into broader application, such as assessing spatial and temporal trends in species diversity associated with environmental stressors. Additionally, because the two parameters of the negative binomial distribution model represent species abundance and evenness of a community, this parametric approach facilitates a deeper understanding of the ecological systems under study. The negative binomial distribution model works with a wide range of species frequency distribution types. As a result, our emphasis on a parametric model can help us characterize the structure of an ecosystem and provide a greater depth of ecologically meaningful information.

Ecological Informatics↗
USGS2014

Integrated conceptual ecological model and habitat indices for the southwest Florida coastal wetlands

The coastal wetlands of southwest Florida that extend from Charlotte Harbor south to Cape Sable, contain more than 60,000 ha of mangroves and 22,177 ha of salt marsh. These coastal wetlands form a transition zone between the freshwater and marine environments of the South Florida Coastal Marine Ecosystem (SFCME). The coastal wetlands provide diverse ecosystem services that are valued by society and thus are important to the economy of the state. Species from throughout the region spend part of their life cycle in the coastal wetlands, including many marine and coastal-dependent species, making this zone critical to the ecosystem health of the Everglades and the SFCME. However, the coastal wetlands are increasingly vulnerable due to rising sea level, changes in storm intensity and frequency, land use, and water management practices. They are at the boundary of the region covered by the Comprehensive Everglades Restoration Plan (CERP), and thus are impacted by both CERP and marine resource management decisions. An integrated conceptual ecological model (ICEM) for the southwest coastal wetlands of Florida was developed that illustrates the linkages between drivers, pressures, ecological process, and ecosystem services. Five ecological indicators are presented: (1) mangrove community structure and spatial extent; (2) waterbirds; (3) prey-base fish and macroinvertebrates; (4) crocodilians; and (5) periphyton. Most of these indicators are already used in other areas of south Florida and the SFCME, and therefore will allow metrics from the coastal wetlands to be used in system-wide assessments that incorporate the entire Greater Everglades Ecosystem.

Ecological Indicators↗
USGS2017

Mercury contamination and stable isotopes reveal variability in foraging ecology of generalist California gulls

Environmental contaminants are a concern for animal health, but contaminant exposure can also be used as a tracer of foraging ecology. In particular, mercury (Hg) concentrations are highly variable among aquatic and terrestrial food webs as a result of habitat- and site-specific biogeochemical processes that produce the bioaccumulative form, methylmercury (MeHg). We used stable isotopes and total Hg (THg) concentrations of a generalist consumer, the California gull ( Larus californicus ), to examine foraging ecology and illustrate the utility of using Hg contamination as an ecological tracer under certain conditions. We identified four main foraging clusters of gulls during pre-breeding and breeding, using a traditional approach based on light stable isotopes. The foraging cluster with the highest δ 15 N and δ 34 S values in gulls (cluster 4) had mean blood THg concentrations 614% (pre-breeding) and 250% (breeding) higher than gulls with the lowest isotope values (cluster 1). Using a traditional approach of stable-isotope mixing models, we showed that breeding birds with a higher proportion of garbage in their diet (cluster 2: 63–82% garbage) corresponded to lower THg concentrations and lower δ 15 N and δ 34 S values. In contrast, gull clusters with higher THg concentrations, which were more enriched in 15 N and 34 S isotopes, consumed a higher proportion of more natural, estuarine prey. δ 34 S values, which change markedly across the terrestrial to marine habitat gradient, were positively correlated with blood THg concentrations in gulls. The linkage we observed between stable isotopes and THg concentrations suggests that Hg contamination can be used as an additional tool for understanding animal foraging across coastal habitat gradients.

Ecological Indicators↗
USGS2019

Selecting ecological models using multi-objective optimization

Choices in ecological research and natural resource management require balancing multiple, often competing objectives. Examples include maximizing species persistence in a wildlife conservation context, while minimizing cost, or balancing opposing stakeholder objectives when managing wildlife populations. Multiple-objective optimization (MOO) provides a unifying framework for solving multiple objective problems. Model selection is a critical component of ecological inference and prediction and requires balancing the competing objectives of model fit and model complexity. The tradeoff between model fit and model complexity provides a basis for describing the model-selection problem within the MOO framework. We discuss MOO and two strategies for solving the MOO problem; modeling preferences pre-optimization and post-optimization. Most conventional model selection methods can be formulated as solutions of MOO problems via specification of pre-optimization preferences. We reconcile model selection within the MOO framework. We also consider model selection using post-optimization specification of preferences. That is, by first identifying Pareto optimal solutions, and then selecting among them. We demonstrate concepts with an ecological application of model selection using avian species richness data in the continental United States.

Ecological Modelling↗
USGS2020

Ecological risk assessment of environmental stress and bioactive chemicals to riverine fish populations: An individual-based model of smallmouth bass Micropterus dolomieu

Ecological risk assessments play an important role in environmental management and decision-making. Although empirical measurements of the effects of habitat changes and chemical exposure are often made at molecular and individual levels, environmental decision-making often requires the quantification of management-relevant, population-level outcomes. In this study, we generalized a modeling framework to evaluate population-level ecological risk of environmental stress and bioactive chemicals. The modeling framework includes (1) a biological model module that incorporates complex and interacting biological and ecological processes, and environmental stochasticity, (2) an effect module that links the impacts of environmental changes and chemical exposure to individual characteristics, and (3) a population module that makes decisions on the choice of population-level properties to best capture the effects and thus to track in the model based on the target species and the research and management interest. This framework is a 3-module procedure that provides an alternative way for researchers to organize, present and communicate the risk assessment modeling studies. To demonstrate this framework, we used a socioeconomically important riverine fish species, smallmouth bass Micropterus dolomieu , as the model species. We developed an individual-based model as the biological model module. We evaluated the impacts of changing water temperature and flow regimes, and the impacts of exposure to estrogenic endocrine disrupting compounds (EEDC) on smallmouth bass populations in the Chesapeake Bay Watershed, USA. Warm summer water temperatures and year-round high flows had the most severe impacts on the smallmouth bass population. An increase in exposure level to EEDC, both year-round and in summer months, substantially reduced population size, spawner and recruit abundance, and the proportion of quality-length individuals. Acute exposure to EEDC was more detrimental to the population than chronic exposure. Acute exposure during spawning season had the most severe impacts. This modeling framework can be extended to other species, environmental factors and chemicals, and can be used to inform management and conservation decisions.

Delaware, Maryland, New York, Pennsylvania, Virgin↗