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Results for “Ecological Modelling”

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At least 1,675 records · Page 93Linked to original sources

USGS2008

A biomonitor for tracking changes in the availability of lakewater cadmium over space and time

Determining the exposure of organisms to contaminants is a key component of Ecological Risk Assessments (ERAs). Effective estimates of exposure consider not only the total concentrations of contaminants in an organism's surroundings but also the availability of the contaminants to organisms. Contaminant availability can be inferred from mechanistic models and verified by measurements of contaminant concentrations in organisms. We evaluated the widespread lake-dwelling insect Chaoborus as a potential biomonitor for use in exposure assessments for three metals: cadmium (Cd), copper (Cu), and zinc (Zn). We show that larvae of this midge maintain constant their concentrations of the essential metals Cu and Zn and thus cannot be used to monitor them. In contrast, larval Cd concentrations varied widely both among lakes and in a given lake over time. We were able to relate these variations in biomonitor Cd to changes in lakewater Cd and pH using the Free Ion Activity Model (FIAM). Our results suggest that Chaoborus larvae could be used as an effective tool for estimating the Cd exposure of organisms in lakes for the purposes of ERAs.

Human and Ecological Risk Assessment↗

USGS2026

Incorporating data sets with multiple sources of uncertainty in integrated species distribution models

Data integration methods aim to improve species distribution estimates by incorporating multiple sources of uncertainty across datasets. Two major sources of uncertainty are: (1) variation in sampling effort across space and within datasets, and (2) variation in reliability associated with data collection protocols or timing among datasets. Our goal was to evaluate how different approaches to address these uncertainties influence predictive performance of integrated models. We modeled distributions of four bird species using three datasets that differed in sampling design. We examined three strategies to reduce uncertainty: (1) filtering data, (2) incorporating functions that account for uncertainty in observation models, and (3) varying how datasets are integrated into a single estimate. We first examine methods to account for variable effort in observations, focusing on both spatial differences in sampling intensity and effort given to a single observation record. We then examine approaches to account for data sets with differing reliability. Sampling effort was best addressed through conservative filtering, including spatial thinning and excluding observations with highly variable effort. Next, we considered how to account for potential false positive detections—due to either misidentification or changes in distributions. We found that treating less reliable data as a covariate, an approach previously suggested for data integration that can greatly speed up model fitting, performed well. Other effective approaches included directly modeling false positive rates and complete exclusion of less reliable data sets. Our results provide insights into best practices in integrated modeling for handling uncertainty in integrated models. We demonstrate the flexible options available when using integrated models to address uncertainty.

Pennsylvania↗

USGS2025

Estimating indicators of cyanobacterial harmful algal blooms in New York State

Cyanobacteria harmful algal blooms (cyanoHABs) are a global concern for aquatic ecosystem and human health. Limited funding for monitoring programs and inconsistent determination of cyanoHAB occurrence present challenges for identifying commonly effective variables for characterizing cyanoHABs and the development of generalized models. We compiled a combination of water quality measurements, lake morphology, climatology, remote sensing data, and observations of cyanoHAB occurrence across New York State and used this dataset to develop two sets of predictive models. The first model predicted chlorophyll a , a common indicator of algal biomass, and assessed the importance of variables for modeled predictions. The most important variables were then used in a second set of models to classify cyanoHAB occurrence. The irradiance attenuation coefficient ( K d ), which was estimated from Secchi depth measurements, and total phosphorus were the two most important variables for predicting chlorophyll a . The second model examined several variables for their ability to classify cyanoHAB occurrence. Predicted cyanoHAB occurrence based on thresholds of chlorophyll a , K d , or total nitrogen all had moderate agreement and were able to correctly classify approximately 70% of observed cyanoHABs. Our analysis indicated that multiple data types were important for predicting chlorophyll a statewide and that simple widely available water quality parameters could classify cyanoHABs occurrence with reasonable accuracy. Identifying variables that can be monitored with increased frequency and decreased latency to detect cyanoHAB occurrence will better inform water managers and provide valuable additional data for further refining predictive models of the likelihood of cyanoHABs occurrence.

New York↗

USGS2021

Global resorption efficiencies of trace elements in leaves of terrestrial plants

Leaf nutrient resorption is a critical nutrient conservation strategy. Previous studies focus mainly on resorption patterns of macronutrients, but resorption patterns of trace elements remain poorly understood. A meta-analysis was conducted to explore the general patterns of the leaf resorption of eight trace elements [i.e. copper (Cu), molybdenum (Mo), zinc (Zn), boron (B), manganese (Mn), sodium (Na), aluminium (Al) and iron (Fe)], and a macronutrient [i.e. sulphur (S)] using data collected from 53 published studies. Sulphur (49.6%) had the highest average resorption efficiency followed by Cu (30.3%), Mo (29.5%), Zn (19.5%) and B (17.6%). Two structural elements, Na and Mn, were not resorbed, whereas two potentially toxic elements, Al (−55.6%) and Fe (−25.4%), were accumulated in senesced leaves. Both climatic factors and growth types affected leaf nutrient resorption efficiency, but the magnitudes and directions of the effects differed greatly between S and the trace elements. The resorption efficiencies of S, Cu, Mo and Zn decreased as leaf nutrient concentrations increased, but the structural or potentially toxic elements (i.e. B, Mn, Na, Fe and Al) presented no response or opposite trends. Our results provide global mean resorption efficiencies of trace elements for the first time, and highlight that structural and potentially toxic elements have relatively lower or no leaf resorption, which should be fully considered in biogeochemical models.

Functional Ecology↗

USGS2014

Accounting for imperfect detection in Hill numbers for biodiversity studies

Hill numbers unify biodiversity metrics by combining several into one expression. For example, species richness, Shannon's diversity index and the Gini–Simpson index are a few of the most used diversity measures, and they can be expressed as Hill numbers. Traditionally, Hill numbers have been calculated from relative abundance data, but the expression has been modified to use incidence data as well. We demonstrate an approach for estimating Hill numbers using an occupancy modelling framework that accounts for imperfect detection. We alter the Hill numbers formula to use occupancy probabilities as opposed to the incidence probabilities that have been used previously and to calculate its summations from the modelled species richness. After introducing the occupancy-based Hill numbers, we demonstrate the differences between them and the incidence-based Hill numbers previously used through a simulation study and two applications. In the simulation study and the two examples using real data, the occupancy-based Hill numbers were larger than the incidence-based Hill numbers, although species richness was estimated similarly using both methods. The occupancy-based Hill number estimators are always at their asymptotic values (i.e. as if an infinite number of samples have been taken for the study region), therefore making it easy to compare biodiversity between different assemblages. In addition, the Hill numbers are computed as derived quantities within a Bayesian hierarchical model, allowing for straightforward inference.

Methods in Ecology and Evolution↗

USGS2000

Sensitivity of species habitat-relationship model performance to factors of scale

Researchers have come to different conclusions about the usefulness of habitat-relationship models for predicting species presence or absence. This difference frequently stems from a failure to recognize the effects of spatial scales at which the models are applied. We examined the effects of model complexity, spatial data resolution, and scale of application on the performance of bird habitat relationship (BHR) models on the Craig Mountain Wildlife Management Area and on the Idaho portion of the U.S. Forest Service's Northern Region. We constructed and tested BHR models for 60 bird species detected on the study areas. The models varied by three levels of complexity (amount of habitat information) and three spatial data resolutions (0.09 ha, 4 ha, 10 ha). We tested these models at two levels of analysis: the site level (a homogeneous area <0.5 ha) and cover-type level (an aggregation of many similar sites of a similar land-cover type), using correspondence between model predictions and species detections to calculate kappa coefficients of agreement. Model performance initially increased as models became more complex until a point was reached where omission errors increased at a rate greater than the rate at which commission errors were decreasing. Heterogeneity of the study areas appeared to influence the effect of model complexity. Changes in model complexity resulted in a greater decrease in commission error than increase in omission error. The effect of Spatial data resolution on the performance of BHR models was influenced by the variability of the study area. BHR models performed better at cover-type levels of analysis than at the site level for both study areas. Correct-presence estimates (1 - minus percentage omission error) decreased slightly as number of species detections increased on each study area. Correct-absence estimates (1 - percentage commission error) increased as number of species detections increased on each study area. This suggests that a large number of detections may be necessary to achieve reliable estimates of model accuracy.

Idaho↗

USGS1989

Postfledging survival of European starlings

We tested the hypotheses that mass at fledging and fledge date within the breeding season affect postfledging survival in European Starlings (Sturnus vulgaris). Nestlings were weighed on day 18 after hatch and tagged with individually identifiable patagial tags. Fledge date was recorded. Marked fledglings were resighted during weekly two—day intensive observation periods for >9 wk postfledging. Postfledging survival and sighting probabilities were estimated for each of four groups (early or late fledging by heavy or light fledging mass). Body mass was related to postfledging survival for birds that fledged early. Results were not clear—cut for relative fledge date, although there was weak evidence that this also influenced survival. Highest survival probability estimates occurred in the EARLY—HEAVY group while the lowest survival estimate occurred in the LATE—NIGHT group. Sighting probabilities differed significantly among groups, emphasizing the need to estimate and compare survival using models which explicitly incorporate sighting probabilities.

Ecology↗

USGS2003

Influence of landscape structure and climate variability on a late holocene plant migration

We analyzed and radiocarbon-dated 205 fossil woodrat middens from 14 sites in central and northern Wyoming and adjacent Utah and Montana to document spatiotemporal patterns of Holocene invasion by Utah juniper (Juniperus osteosperma). Holocene migration into central and northern Wyoming and southern Montana from the south proceeded by a series of long-distance dispersal events, which were paced by climate variability and structured by the geographic distribution and connectivity of suitable habitats on the landscape. The migration of Utah juniper into the region involved multiple long-distance dispersal events, ranging from 30 to 135 km. One of the earliest established populations, on East Pryor Mountain in south central Montana, is currently the northernmost population of the species. Establishment by long-distance dispersal of that population and another in the Bighorn Basin occurred during a period of relatively dry climate between 7500 and 5400 years ago. Further expansion of these initial colonizing populations and backfilling to occupy suitable sites to the south was delayed during a wet period from 5400 to 2800 years ago. Development of dry conditions 2800 years ago led to a rapid expansion in which Utah juniper colonized sites throughout its current range. Landscape structure and climate variability play important roles in governing the pattern and pace of natural invasions and deserve close attention in studying and modeling plant invasions, whether exotic or natural.

Ecological Monographs↗

USGS2002

Ecological and evolutionary conditions for fruit abortion to regulate pollinating seed-eaters and increase plant production

Coevolved mutualisms, such as those between senita cacti, yuccas, and their respective obligate pollinators, benefit both species involved in the interaction. However, in these pollination mutualisms the pollinator's larvae impose a cost on plants through consumption of developing seeds and fruit. The effects of pollinators on benefits and costs are expected to vary with the abundance of pollinators, because large population sizes result in more eggs and larval seed-eaters. Here, we develop the hypothesis that fruit abortion, which is common in yucca, senita, and plants in general, could in some cases have the function of limiting pollinator abundance and, thereby, increasing fruit production. Using a general steady-state model of fruit production and pollinator dynamics, we demonstrate that plants involved in pollinating seed-eater mutualisms can increase their fecundity by randomly aborting fruit. We show that the ecological conditions under which fruit abortion can improve plants fecundity are not unusual. They are best met when the plant is long-lived, the population dynamics of the pollinator are much faster than those of the plant, the loss of one fruit via abortion kills a larva that would have the expectation of destroying more than one fruit through its future egg laying as an adult moth, and the effects of fruit abortion on pollinator abundance are spatially localized. We then use the approach of adaptive dynamics to find conditions under which a fruit abortion strategy based on regulating the pollinator population could feasibly evolve in this type of plant–pollinator interaction.

Theoretical Population Biology↗

USGS2004

Detecting warning signs of trouble within population fluctuations: using capture-recapture modeling to uncover changes in population dynamics leading to declines

An intensive mark-recapture/resighting program has been carried out on the Roseate Terns nesting at Falkner Island, Connecticut, since the late 1980s as part of a regional study of the metapopulation dynamics and ecology of the endangered Northwest Atlantic breeding population of this species. Substantial losses of tern eggs and chicks to predation at this colony site began in 1996 when at least five Black-crowned Night-Herons started nocturnal raids. This depredation has been a major factor in the reduction of productivity from an average of about 1.0 chicks/pair for the 10 years before night-heron predation began to as low as about 0.2 chicks/pair in 2002. Recent capture-recapture modelling analyses have detected other important impacts on the population dynamics of the Roseate Terns at this site including a reduction by about half in the 'development-of-residency' rates of first-time breeders, and a substantial decline in the local 'survival-and-fidelity' rates of experienced breeders believed due mostly to increased immigration rates to other colony sites.

Annual Meeting of the Association of Field Ornitho↗

USGS2019

Reduced soil macropores and forest cover reduce warm-season baseflow below ecological thresholds in the upper Delaware River Basin

We examined the impacts of changes in land cover and soil conditions on the flow regime of the upper Delaware River Basin using the Water Availability Tool for Environmental Resources (WATER). We simulated flows for two periods, circa 1600 and 1940, at three sites using the same temperature and precipitation conditions: the East Branch (EB), West Branch (WB), and mainstem Delaware River at Callicoon, NY. The 1600 period represented pristine forest and soils. The 1940 period included reduced forest cover, increased agriculture, and degraded soils with reduced soil macropore fractions. A model-sensitivity test examined the impact of soil macropore and land cover change separately. We assessed changes in flow regimes between the 1600 and 1940 periods using a variety of flow statistics, including established ecological limits of hydrologic alteration (ELOHA) thresholds. Reduced forest soil macropore fraction significantly reduced summer and fall base flows. The 1940 period had significantly lower Q50 flows (50% exceedance) than the 1600 period, as well as summer and fall Q90 and Q75-90 flows below the ELOHA thresholds. The 1- to 7-day minimum flows were also lower for the 1940 period, by 17% on the mainstem. 1940 flows were 6% more likely than the 1600 period to fall below the low-flow threshold for federally endangered dwarf wedgemussel (Alasmidonta heterodon) habitat. In contrast, the 1940 period had higher flows than the 1600 period from late fall to early winter.

New York, Pennsylvania↗

USGS2010

Environmental controls on drainage behavior of an ephemeral stream

Streambed drainage was measured at the cessation of 26 ephemeral streamflow events in Rillito Creek, Tucson, Arizona from August 2000 to June 2002 using buried time domain reflectometry (TDR) probes. An unusual drainage response was identified, which was characterized by sharp drainage from saturation to near field capacity at each depth with an increased delay between depths. We simulated the drainage response using a variably saturated numerical flow model representing a two-layer system with a high permeability layer overlying a lower permeability layer. Both the observed data and the numerical simulation show a strong correlation between the drainage velocity and the temperature of the stream water. A linear combination of temperature and the no-flow period preceding flow explained about 90% of the measured variations in drainage velocity. Evaluation of this correlative relationship with the one-dimensional numerical flow model showed that the observed temperature fluctuations could not reproduce the magnitude of variation in the observed drainage velocity. Instead, the model results indicated that flow duration exerts the most control on drainage velocity, with the drainage velocity decreasing nonlinearly with increasing flow duration. These findings suggest flow duration is a primary control of water availability for plant uptake in near surface sediments of an ephemeral stream, an important finding for estimating the ecological risk of natural or engineered changes to streamflow patterns. Correlative analyses of soil moisture data, although easy and widely used, can result in erroneous conclusions of hydrologic cause—effect relationships, and demonstrating the need for joint physically-based numerical modeling and data synthesis for hypothesis testing to support quantitative risk analysis.

Arizona↗

USGS2013

Climate change's impact on key ecosystem services and the human well-being they support in the US

Climate change alters the functions of ecological systems. As a result, the provision of ecosystem services and the well-being of people that rely on these services are being modified. Climate models portend continued warming and more frequent extreme weather events across the US. Such weather-related disturbances will place a premium on the ecosystem services that people rely on. We discuss some of the observed and anticipated impacts of climate change on ecosystem service provision and livelihoods in the US. We also highlight promising adaptive measures. The challenge will be choosing which adaptive strategies to implement, given limited resources and time. We suggest using dynamic balance sheets or accounts of natural capital and natural assets to prioritize and evaluate national and regional adaptation strategies that involve ecosystem services.

Frontiers in Ecology and the Environment↗

USGS2011

Baseline ecological risk assessment of the Calcasieu Estuary, Louisiana: 1. Overview and problem formulation

A remedial investigation/feasibility study (RI/FS) of the Calcasieu Estuary cooperative site was initiated in 1998. This site, which is located in the southwestern portion of Louisiana in the vicinity of Lake Charles, includes the portion of the estuary from the saltwater barrier on the Calcasieu River to Moss Lake. As part of the RI/FS, a baseline ecological risk assessment (BERA) was conducted to assess the risks to aquatic organisms and aquatic-dependent wildlife exposed to environmental contaminants. The purpose of the BERA was to determine if adverse effects on ecological receptors are occurring in the estuary; to evaluate the nature, severity, and areal extent of any such effects; and to identify the substances that are causing or substantially contributing to effects on ecological receptors. This article describes the environmental setting and site history, identifies the chemicals of potential concern, presents the exposure scenarios and conceptual model for the site, and summarizes the assessment and measurement endpoints that were used in the investigation. Two additional articles in this series describe the results of an evaluation of effects-based sediment-quality guidelines as well as an assessment of risks to benthic invertebrates associated with exposure to contaminated sediment.

Louisiana↗

USGS2020

Non-analog increases to air, surface, and belowground temperature extreme events due to climate change

Air temperatures (Ta) are rising in a changing climate, increasing extreme temperature events. Examining how Ta increases are influencing extreme temperatures at the soil surface and belowground in the soil profile can refine our understanding of the ecological consequences of rising temperatures. In this paper, we validate surface and soil temperature (Ts: 0–100-cm depth) simulations in the SOILWAT2 model for 29 locations comprising 5 ecosystem types in the central and western USA. We determine the temperature characteristics of these locations from 1980 to 2015, and explore simulations of Ta and Ts change over 2030–2065 and 2065–2100 time periods using General Circulation Model (GCM) projections and the RCP 8.5 emissions scenario. We define temperature extremes using a nonstationary peak over threshold method, quantified from standard deviations above the mean (0- σ : an event >∼ "> >∼ >∼ 51% of extreme events; 2- σ :>∼ 98 % "> σ :>∼ 98 % σ:>∼98% ). Our primary objective is to contrast the magnitude ( ∘ C) and frequency of occurrence of extreme temperature events between the twentieth and twenty-first century. We project that temperatures will increase substantially in the twenty-first century. Extreme Ta events will experience the largest increases by magnitude, and extreme Ts events will experience the largest increases by proportion. On average, 2- σ extreme Ts events will increase by 3.4 ∘ C in 2030–2065 and by 5.3 ∘ C in 2065–2100. Increases in extreme Ts events will often exceed + 10 ∘ C at 0–20 cm by 2065–2100, and at 0–100 cm will often exceed 5.0 standard deviations above 1980–2015 values. 2- σ extreme Ts events will increase from 0.9 events per decade in 1980–2015 to 23 events in 2030–2065 and 38 events in 2065–2100. By 2065–2100, the majority of months will experience extreme events that co-occur at 0–100 cm, which did not occur in 1980–2015. These projections illustrate the non-analog temperature increases that ecosystems will experience in the twenty-first century as a result of climate change.

Climate Change↗

USGS2019

Perspective: Developing flow policies to balance the water needs of humans and wetlands requires a landscape scale approach inclusive of future scenarios and multiple timescales

Maintenance of the natural flow regime is essential for continued wetland integrity; however, the flow regime is greatly influenced by both natural and anthropogenic forces. Wetlands may be particularly susceptible to altered flow regimes as they are directly impacted by water flows at a variety of time scales. In Puerto Rico, contemporary water management is decreasing freshwater recharge to wetlands and contributes to the salinization of important coastal wetlands as sea levels rise. Further, downscaled climate models predict an increase in drought frequency, intensity, and duration by mid-century. Conflicts over water allocation seem imminent between human and ecological needs. Current minimum flow policies are insufficient given the complexities of ecosystem processes and the changes in precipitation patterns and sea level rise that are expected in the future. Improved flow policies need to be established that reflect the functional relationships between specific representative ecological resources and components of the natural flow regime across all relevant time scales. Similarly, flow policies need to be developed within a landscape scale to implicitly address the socio-ecological trade-offs as well as the complexities of water management. Multi-disciplinary collaborations will be essential for increasing our resiliency to anticipated future changes.

Wetlands↗

USGS2025

Reevaluation of an adaptive management framework for invasive Grass Carp within Lake Erie

Objective Response efforts to control invasive species frequently require making decisions in the face of substantial uncertainty. Adaptive management, which emphasizes learning during the process of managing, can be useful in cases where uncertainty impedes the decision-making process. Here, we describe how technical and institutional learning led to reformulating decision-making elements, known as double-loop learning, and how uncertainty stemming from a lack of knowledge influenced the selection of alternative strategies in an ongoing adaptive management process for invasive Grass Carp Ctenopharyngodon idella in Lake Erie. Methods When response efforts began, little was known about the population dynamics, ecology, and biology of Grass Carp within the lake. The availability of funding for sustained response efforts was also unknown. A network population model was constructed that relied heavily on values and estimates from limited data to project adult Grass Carp abundance in Lake Erie and evaluate the ability of various response strategies to achieve the desired objectives. After this initial assessment, the collection of new information was emphasized as response efforts increased to aid future assessments. With this expanded knowledge and including additional input from stakeholders, we modified the population model, evaluated new response scenarios, refined objectives, and examined the influence of uncertainty (parameter and expert opinion) on Grass Carp response efforts. Results Under uncertainty of population model parameters and expert opinion, the value-of-information analysis revealed that uncertainties in spawning deterrent efficacy, survival, and the underlying stock–recruitment relationship were important and could change the preferred decision. The efficiency of spawning deterrents influenced the preferred decision outcome among alternative strategies, particularly when >80% of fish were allowed to pass and spawn, indicating that a deterrent may not be worth implementing if passing rates are above this threshold. Conclusions We thereby demonstrate the benefits for invasive species management programs of implementing learning and resolving uncertainties within an adaptive management framework to improve decision making.

Lake Erie↗

USGS2017

Host susceptibility to snake fungal disease is highly dispersed across phylogenetic and functional trait space

Emerging infectious diseases (EIDs) reduce host population sizes, cause extinction, disassemble communities, and have indirect negative effects on human well-being. Fungal EIDs have reduced population abundances in amphibians and bats across many species over large areas. The recent emergence of snake fungal disease (SFD) may have caused declines in some snake populations in the Eastern United States (EUS), which is home to a phylogenetically and ecologically diverse assembly of 98 taxa. SFD has been documented in only 23 naturally occuring species, although this is likely an underestimate of the number of susceptible taxa. Using several novel methods, including artificial neural networks, we combine phylogenetic and trait-based community estimates from all taxa in this region to show that SFD hosts are both phylogenetically and ecologically randomly dispersed. This might indicate that other species of snakes in the EUS could be currently infected or susceptible to SFD. Our models also indicate that information about key traits that enhance susceptiblity is lacking. Surveillance should consider that all snake species and habitats likely harbor this pathogen.

Science Advances↗