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At least 1,225 records · Page 68Linked to original sources
USGS2022

Biogeography of freshwater mussels (Bivalvia: Unionida) in Texas and implications on conservation biology

Aim Biogeography seeks to identify and explain the spatial distributions of species and has become an important tool used by conservationists to protect and manage aquatic organisms. Texas, located in the southwestern United States, is home to 52 species of freshwater mussels, 9 of which are endemic to Texas and 7 that are endemic to Texas and neighboring states or countries. There have been two major attempts to classify this fauna into biogeographical provinces; however, both efforts relied on limited distribution information and outdated taxonomy. To address both issues, we set out to delineate biogeographic provinces for freshwater mussels in Texas by using a comprehensive distributional dataset of >28,000 records and molecular information. Location Southwestern United States. Methods We compiled community and molecular data for 48 of the 52 freshwater mussel species that occur in Texas. We performed algorithmic hierarchal cluster analysis (HCA) and nonmetric multidimensional scaling (NMDS) based on Euclidean distance to identify biogeographic groupings. We conducted a similar analysis using molecular sequence data for our target species. Results Based on the results from community and molecular data, we identified seven biogeographic provinces for freshwater mussels in Texas: Great Plains, Mississippi Embayment, Sabine-Neches, Trinity-San Jacinto, Central Texas, Rio Grande and Coastal. However, the Coastal and Great Plains provinces were not included in our analysis and were recognized based on previous work. Main conclusions Our approach integrating community and molecular datasets provides a comprehensive assessment of the biogeography of freshwater mussels in Texas, which serves as a model for future biogeographic studies. Our findings also shed light on the ecological, evolutionary and geologic processes shaping freshwater mussel communities in Texas, which is important for the conservation of remaining biodiversity in the state.

Texas↗
USGS2026

Adaptation and response in drylands: A dryland research agenda and campaign strategy

Dryland ecosystems cover 41% of Earth's land surfaces, account for 44% of cultivated lands and 60% of food sources, and make large contributions to the global water and carbon cycles. However, these ecosystems are experiencing unprecedented extremes including heatwaves, floods, and droughts as well as hotter temperatures and often declining water resource availability. These ecosystems are some of the most challenging to monitor given their high temporal variability with rapid response to their environment as well as vast spatial variability with intermixing of different plant species and life forms amongst bare soil coverage. The Adaptation and Response in Drylands (ARID) campaign was selected by National Aeronautics and Space Administration (NASA) as a scoping study to develop a research agenda for a dryland field campaign. Here, we detail our ARID science research agenda and implementation plan that were developed based on an extensive community engagement effort in over 160 events with over a thousand scientists, land managers, and Tribal communities between 2023 and 2024. The selected science themes cover drought and climate variability, ecosystem structure, function, and biodiversity, carbon cycle interannual variability and trends, and social ecological systems (land management and adaptation). We then detail our remote sensing, modeling, and field-based strategies to capture high temporal and high spatial resolution processes. Finally, our implementation strategy is presented which includes focus area selections in a core intensive western U.S. domain and distributed international domains. This strategy includes our overarching guiding principles of using multi-temporal airborne acquisitions and super sites as well as enhancing land management in co-development with end-user partners. While originally developed for NASA, our ARID report creates a blueprint for any future dryland field campaign, at any scale, that can be implemented widely for foundational and applied science objectives.

Global Change Biology↗
USGS2008

A quantile count model of water depth constraints on Cape Sable seaside sparrows

1. A quantile regression model for counts of breeding Cape Sable seaside sparrows Ammodramus maritimus mirabilis (L.) as a function of water depth and previous year abundance was developed based on extensive surveys, 1992-2005, in the Florida Everglades. The quantile count model extends linear quantile regression methods to discrete response variables, providing a flexible alternative to discrete parametric distributional models, e.g. Poisson, negative binomial and their zero-inflated counterparts. 2. Estimates from our multiplicative model demonstrated that negative effects of increasing water depth in breeding habitat on sparrow numbers were dependent on recent occupation history. Upper 10th percentiles of counts (one to three sparrows) decreased with increasing water depth from 0 to 30 cm when sites were not occupied in previous years. However, upper 40th percentiles of counts (one to six sparrows) decreased with increasing water depth for sites occupied in previous years. 3. Greatest decreases (-50% to -83%) in upper quantiles of sparrow counts occurred as water depths increased from 0 to 15 cm when previous year counts were 1, but a small proportion of sites (5-10%) held at least one sparrow even as water depths increased to 20 or 30 cm. 4. A zero-inflated Poisson regression model provided estimates of conditional means that also decreased with increasing water depth but rates of change were lower and decreased with increasing previous year counts compared to the quantile count model. Quantiles computed for the zero-inflated Poisson model enhanced interpretation of this model but had greater lack-of-fit for water depths > 0 cm and previous year counts 1, conditions where the negative effect of water depths were readily apparent and fitted better with the quantile count model.

Journal of Animal Ecology↗
USGS2011

Structural complexity, movement bias, and metapopulation extinction risk in dendritic ecological networks

Spatial complexity in metacommunities can be separated into 3 main components: size (i.e., number of habitat patches), spatial arrangement of habitat patches (network topology), and diversity of habitat patch types. Much attention has been paid to lattice-type networks, such as patch-based metapopulations, but interest in understanding ecological networks of alternative geometries is building. Dendritic ecological networks (DENs) include some increasingly threatened ecological systems, such as caves and streams. The restrictive architecture of dendritic ecological networks might have overriding implications for species persistence. I used a modeling approach to investigate how number and spatial arrangement of habitat patches influence metapopulation extinction risk in 2 DENs of different size and topology. Metapopulation persistence was higher in larger networks, but this relationship was mediated by network topology and the dispersal pathways used to navigate the network. Larger networks, especially those with greater topological complexity, generally had lower extinction risk than smaller and less-complex networks, but dispersal bias and magnitude affected the shape of this relationship. Applying these general results to real systems will require empirical data on the movement behavior of organisms and will improve our understanding of the implications of network complexity on population and community patterns and processes.

Journal of the North American Benthological Societ↗
USGS2013

Serious games experiment toward agent-based simulation

We evaluate the potential for serious games to be used as a scientifically based decision-support product that supports the United States Geological Survey’s (USGS) mission--to provide integrated, unbiased scientific information that can make a substantial contribution to societal well-being for a wide variety of complex environmental challenges. Serious or pedagogical games are an engaging way to educate decisionmakers and stakeholders about environmental challenges that are usefully informed by natural and social scientific information and knowledge and can be designed to promote interactive learning and exploration in the face of large uncertainties, divergent values, and complex situations. We developed two serious games that use challenging environmental-planning issues to demonstrate and investigate the potential contributions of serious games to inform regional-planning decisions. Delta Skelta is a game emulating long-term integrated environmental planning in the Sacramento-San Joaquin Delta, California, that incorporates natural hazards (flooding and earthquakes) and consequences for California water supplies amidst conflicting water interests. Age of Ecology is a game that simulates interactions between economic and ecologic processes, as well as natural hazards while implementing agent-based modeling. The content of these games spans the USGS science mission areas related to water, ecosystems, natural hazards, land use, and climate change. We describe the games, reflect on design and informational aspects, and comment on their potential usefulness. During the process of developing these games, we identified various design trade-offs involving factual information, strategic thinking, game-winning criteria, elements of fun, number and type of players, time horizon, and uncertainty. We evaluate the two games in terms of accomplishments and limitations. Overall, we demonstrated the potential for these games to usefully represent scientific information within challenging environmental and ecosystem-management contexts and to provide an interactive way of learning about the complexity of interactions between people and natural systems. Further progress on the use of pedagogical games to fulfill the USGS mission will require collaboration among scientists, game developers, educators, and stakeholders. We conclude that as the USGS positions itself to communicate and convey the results of multiple science strategies, including natural-resource security and sustainability, pedagogical game development and agent-based modeling offer a means to (1) establish interdisciplinary and collaborative teams with a focused integrated outcome; (2) contribute to the modeling of interaction, feedback, and adaptation of ecosystems; and (3) enable social learning through a broadly appealing and increasingly sophisticated medium.

Open-File Report↗
USGS2002

Contrasting determinants of abundance in ancestral and colonized ranges of an invasive brood parasite

Avian species distributions are typically regarded as constrained by spatially extensive variables such as climate, habitat, spatial patchiness, and microhabitat attributes. We hypothesized that the distribution of a brood parasite depends as strongly on host distribution patterns as on biophysical factors and examined this hypothesis with respect to the national distribution of the Brown-headed Cowbird (Molothrus ater). We applied a classification and regression (CART) analysis to data from the Breeding Bird Survey (BBS) and the Christmas Bird Count (CBC) and derived hierarchically organized statistical models of the influence of climate and weather, cropping and land use, and host abundance and distribution on the distribution of the Brown-headed Cowbird within the conterminous United States. The model accounted for 47.2% of the variation in cowbird incidence, and host abundance was the top predictor with an R2 of 18.9%. The other predictors identified by the model (crops 15.7%, weather and climate 14.3%, and region 9.6%) fit the ecological profile of this cowbird. We showed that host abundance was independent of these environmental predictors of cowbird distribution. At the regional scale host abundance played a very strong role in determining cowbird abundance in the cowbird?s colonized range east and west of their ancestral range in the Great Plains (26.6%). Crops were not a major predictor for cowbirds in their ancestral range, although they are the most important predictive factor (33%) for the grassland passerines that are the cowbird?s ancestral hosts. Consequently our findings suggest that the distribution of hosts does indeed take precedence over habitat attributes in shaping the cowbird?s distribution at a national scale, within an envelope of constraint set by biophysical factors.

Book chapter↗
USGS2013

Potential effects of climate change on inland glacial lakes and implications for lake-dependent biota in Wisconsin: final report April 2013

The economic vitality and quality of life of many northern Wisconsin communities is closely associated with the ecological condition of the abundant water resources in the region. Climate change models predict warmer temperatures, changes to precipitation patterns, and increased evapotranspiration in the Great Lakes region. Recently (1950-2006), many regions of Wisconsin have experienced warming, and precipitation has generally increased except in far northern Wisconsin. Modeling conducted by the University of Wisconsin Nelson Environmental Institute Center for Climate Research predicts an increase in annual temperature by the middle of the 21st century of approximately 6° F statewide, and an increase in precipitation of 1”–2”. However, summer precipitation in the northern part of the state is expected to be less and winter precipitation will be greater. By the end of the 21st century, the magnitude of changes in temperature and precipitation are expected to intensify. Such climatic changes have altered, and would further alter hydrological, chemical, and physical properties of inland lakes. Lake-dependent wildlife sensitive to changes in water quality, are particularly susceptible to lake quality-associated habitat changes and are likely to suffer restrictions to current breeding distributions under some climate change scenarios. We have selected the common loon (Gavia immer) to serve as a sentinel lake-dependent piscivorous species to be used in the development of a template for linking primary lake-dependent biota endpoints (e.g., decline in productivity and/or breeding range contraction) to important lake quality indicators. In the current project, we evaluate how changes in freshwater habitat quality (specifically lake clarity) may impact common loon lake occupancy in Wisconsin under detailed climate-change scenarios. In addition, we employ simple land-use/land cover and habitat scenarios to illustrate the potential interaction of climate and land-use/land cover effects. The methods employed here provide a template for studies where integration of physical and biotic models is used to project future conditions under various climate and land use change scenarios. Findings presented here project the future conditions of lakes and loons within an important watershed in northern Wisconsin – of importance to water resource managers and state citizens alike.

Wisconsin↗
USGS2004

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895—1993 on a 0.5° latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers.

Climate Research↗
USGS2009

Simulating the recovery of suspended sediment transport and river-bed stability in response to dam removal on the Elwha River, Washington

U.S. Department of the Interior is planning to remove two high dams (30 and 60 m) from the Elwha River, which will allow the river to erode sediment deposits in the reservoirs, and ultimately restore the river ecosystem. Fluvial sediment transport and deposition paradoxically represent ecological disturbance and restoration. A one-dimensional, movable boundary sediment-transport model was applied at a daily time step to simulate changes in river-bed elevations and particle-size distributions and concentrations of suspended sediment. The simulations included a three-year dam removal period and a four-year recovery period. Simulated concentrations of suspended sediment recover rapidly during the recovery period. Simulated bed elevation and particle-size distributions are stable for much of the river during the recovery period, but high flows periodically disturb the river bed, causing changes in river-bed elevation and particle-size distribution, especially during autumn, when summer/autumn chinook salmon are incubating in redds. Although the river bed will become increasingly stable after dam removal, episodic high flows will interrupt recovery trends. Productivity and diversity of the ecosystem may be lower because of excess sediment immediately after dam removal but should increase during recovery above current levels as the river. Monitoring of the recovery of the Elwha River ecosystem can target ecologically significant physical parameters indicating the transition from a sediment transport-limited state to a supply-limited state.

Ecological Engineering↗
USGS2016

Species traits and catchment-scale habitat factors influence the occurrence of freshwater mussel populations and assemblages

Conservation of freshwater unionid mussels presents unique challenges due to their distinctive life cycle, cryptic occurrence and imperilled status. Relevant ecological information is urgently needed to guide their management and conservation. We adopted a modelling approach, which is a novel application to freshwater mussels to enhance inference on rare species, by borrowing data among species in a hierarchical framework to conduct the most comprehensive occurrence analysis for freshwater mussels to date. We incorporated imperfect detection to more accurately examine effects of biotic and abiotic factors at multiple scales on the occurrence of 14 mussel species and the entire assemblage of the Tar River Basin of North Carolina, U.S.A. The single assemblage estimate of detection probability for all species was 0.42 (95% CI, 0.36–0.47) with no species- or site-specific detection effects identified. We empirically observed 15 mussel species in the basin but estimated total species richness at 21 (95% CI, 16–24) when accounting for imperfect detection. Mean occurrence probability among species ranged from 0.04 (95% CI, 0.01–0.16) for Alasmidonta undulata, an undescribed Lampsilis sp. , and Strophitus undulatus to 0.67 (95% CI, 0.42–0.86) for Elliptio icterina . Median occurrence probability among sites was <0.30 for all species with the exception of E. icterina . Site occurrence probability generally related to mussel conservation status, with reduced occurrence for endangered and threatened species. Catchment-scale abiotic variables (stream power, agricultural land use) and species traits (brood time, host specificity, tribe) influenced the occurrence of mussel assemblages more than reach- or microhabitat-scale features. Our findings reflect the complexity of mussel ecology and indicate that habitat restoration alone may not be adequate for mussel conservation. Catchment-scale management can benefit an entire assemblage, but species-specific strategies may be necessary for successful conservation. The hierarchical multispecies modelling approach revealed findings that could not be elucidated by other means, and the approach may be applied more broadly to other river basins and regions. Accurate measures of assemblage dynamics, such as occurrence and species richness, are required to create management plans for effective conservation.

Freshwater Biology↗
USGS2013

Phenology-based, remote sensing of post-burn disturbance windows in rangelands

Wildland fire activity has increased in many parts of the world in recent decades. Ecological disturbance by fire can accelerate ecosystem degradation processes such as erosion due to combustion of vegetation that otherwise provides protective cover to the soil surface. This study employed a novel ecological indicator based on remote sensing of vegetation greenness dynamics (phenology) to estimate variability in the window of time between fire and the reemergence of green vegetation. The indicator was applied as a proxy for short-term, post-fire disturbance windows in rangelands; where a disturbance window is defined as the time required for an ecological or geomorphic process that is altered to return to pre-disturbance levels. We examined variability in the indicator determined for time series of MODIS and AVHRR NDVI remote sensing data for a database of ∼100 historical wildland fires, with associated post-fire reseeding treatments, that burned 1990–2003 in cold desert shrub steppe of the Great Basin and Columbia Plateau of the western USA. The indicator-based estimates of disturbance window length were examined relative to the day of the year that fires burned and seeding treatments to consider effects of contemporary variability in fire regime and management activities in this environment. A key finding was that contemporary changes of increased length of the annual fire season could have indirect effects on ecosystem degradation, as early season fires appeared to result in longer time that soils remained relatively bare of the protective cover of vegetation after fires. Also important was that reemergence of vegetation did not occur more quickly after fire in sites treated with post-fire seeding, which is a strategy commonly employed to accelerate post-fire vegetation recovery and stabilize soil. Future work with the indicator could examine other ecological factors that are dynamic in space and time following disturbance – such as nutrient cycling, carbon storage, microbial community composition, or soil hydrology – as a function of disturbance windows, possibly using simulation modeling and historical wildfire information.

California;Idaho;Nevada;Oregon;Utah;Washington↗
USGS2014

Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches

As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the U.S. Geological Survey (USA), HDR⎪HydroQual, Inc. (USA), and the Centre for Ecology and Hydrology (UK) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME Workshop in Brussels, Belgium (May 2012), is provided herein. Overall, the models were found to be similar in structure (free ion activities computed by WHAM; specific or non-specific binding of metals/cations in or on the organism; specification of metal potency factors and/or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single versus multiple types of binding site on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong inter-relationships among the model parameters (log KM values, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed.

Environmental Toxicology and Chemistry↗
USGS2009

Dynamic models for problems of species occurrence with multiple states

Recent extensions of occupancy modeling have focused not only on the distribution of species over space, but also on additional state variables (e.g., reproducing or not, with or without disease organisms, relative abundance categories) that provide extra information about occupied sites. These biologist-driven extensions are characterized by ambiguity in both species presence and correct state classification, caused by imperfect detection. We first show the relationships between independently published approaches to the modeling of multistate occupancy. We then extend the pattern-based modeling to the case of sampling over multiple seasons or years in order to estimate state transition probabilities associated with system dynamics. The methodology and its potential for addressing relevant ecological questions are demonstrated using both maximum likelihood (occupancy and successful reproduction dynamics of California Spotted Owl) and Markov chain Monte Carlo estimation approaches (changes in relative abundance of green frogs in Maryland). Just as multistate capture–recapture modeling has revolutionized the study of individual marked animals, we believe that multistate occupancy modeling will dramatically increase our ability to address interesting questions about ecological processes underlying population-level dynamics.

Ecology↗
USGS2011

Host and viral ecology determine bat rabies seasonality and maintenance

Rabies is an acute viral infection that is typically fatal. Most rabies modeling has focused on disease dynamics and control within terrestrial mammals (e.g., raccoons and foxes). As such, rabies in bats has been largely neglected until recently. Because bats have been implicated as natural reservoirs for several emerging zoonotic viruses, including SARS-like corona viruses, henipaviruses, and lyssaviruses, understanding how pathogens are maintained within a population becomes vital. Unfortunately, little is known about maintenance mechanisms for any pathogen in bat populations. We present a mathematical model parameterized with unique data from an extensive study of rabies in a Colorado population of big brown bats (Eptesicus fuscus) to elucidate general maintenance mechanisms. We propose that life history patterns of many species of temperate-zone bats, coupled with sufficiently long incubation periods, allows for rabies virus maintenance. Seasonal variability in bat mortality rates, specifically low mortality during hibernation, allows long-term bat population viability. Within viable bat populations, sufficiently long incubation periods allow enough infected individuals to enter hibernation and survive until the following year, and hence avoid an epizootic fadeout of rabies virus. We hypothesize that the slowing effects of hibernation on metabolic and viral activity maintains infected individuals and their pathogens until susceptibles from the annual birth pulse become infected and continue the cycle. This research provides a context to explore similar host ecology and viral dynamics that may explain seasonal patterns and maintenance of other bat-borne diseases.

Proceedings of the National Academy of Sciences of↗
USGS2008

Using an ecological ethics framework to make decisions about the relocation of wildlife

Relocation is an increasingly prominent conservation tool for a variety of wildlife, but the technique also is controversial, even among conservation practitioners. An organized framework for addressing the moral dilemmas often accompanying conservation actions such as relocation has been lacking. Ecological ethics may provide such a framework and appears to be an important step forward in aiding ecological researchers and biodiversity managers to make difficult moral choices. A specific application of this framework can make the reasoning process more transparent and give more emphasis to the strong sentiments about non-human organisms held by many potential users. Providing an example of the application of the framework may also increase the appeal of the reasoning process to ecological researchers and biodiversity managers. Relocation as a conservation action can be accompanied by a variety of moral dilemmas that reflect the interconnection of values, ethical positions, and conservation decisions. A model that is designed to address moral dilemmas arising from relocation of humans provides/demonstrates/illustrates a possible way to apply the ecological ethics framework and to involve practicing conservationists in the overall decision-making process. ?? 2008 Springer Science+Business Media B.V.

Science and Engineering Ethics↗
USGS2025

The transition from resistance to acceptance: Managing a marine invasive species in a changing world

Marine invasive species can transform coastal ecosystems, yet mitigating their effects can be difficult, and even impractical. Often, marine invasive species are managed at poorly matched spatial scales, and at the same time, rates of spread and establishment are increasing under climate change and can outpace resources available for population suppression. These circumstances challenge traditional conservation goals of maintaining a historic environmental state, especially for a species like the European green crab ( Carcinus maenas ), a formidable invader with few examples of successful long-term removal programs. A management paradigm where decision alternatives include resisting or accepting a new ecological trajectory may be needed. We apply mathematical concepts from decision theory to develop a quantitative framework for navigating management decisions in this new resist-accept paradigm. We develop a model of European green crab growth, removal and colonization, and we find optimal levels of removal effort that minimize both ecological change and removal cost. We establish a benchmark of colonization pressure at which green crab density becomes decoupled from a decision maker's actions, such that population control can no longer shape the invasion trajectory. For informing the decision boundary between resistance and acceptance, our results highlight that a decision maker's understanding of how removal cost scales with removal effort is more important than understanding the density-impact relationship. We show that assuming stationary system dynamics can result in sub-optimal levels of species removal effort, highlighting the importance of developing anticipatory management strategies by accounting for non-stationary dynamics. Policy implications . For marine invasive species that can disperse across long distances and recolonize rapidly after removal, the focus of conservation policy should shift away from understanding how to resist change to understanding when to stop resisting change. Navigating this decision problem involves trade-offs among competing objectives, highlighting the need for structured approaches to elicit objective weights that reflect the values of the decision maker. For natural resource managers facing possible ecosystem transformation, this decision framework can enable proactive and strategic decisions made under uncertainty in a changing world.

Journal of Applied Ecology↗
USGS2022

A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms

The Biological Condition Gradient (BCG) is a conceptual model used to describe incremental changes in biological condition along a gradient of increasing anthropogenic stress. As coral reefs collapse globally, scientists and managers are focused on how to sustain the crucial structure and functions, and the benefits that healthy coral reef ecosystems provide for many economies and societies. We developed a numeric (quantitative) BGC model for the coral reefs of Puerto Rico and the US Virgin Islands to transparently facilitate ecologically meaningful management decisions regarding these fragile resources. Here, reef conditions range from natural, undisturbed conditions to severely altered or degraded conditions. Numeric decision rules were developed by an expert panel for scleractinian corals and other benthic assemblages using multiple attributes to apply in shallow-water tropical fore reefs with depths <30 m. The numeric model employed decision rules based on metrics (e.g., % live coral cover, coral species richness, pollution-sensitive coral species, unproductive and sediment substrates, % cover by Orbicella spp.) used to assess coral reef condition. Model confirmation showed the numeric BCG model predicted the panel’s median site ratings for 84% of the sites used to calibrate the model and 89% of independent validation sites. The numeric BCG model is suitable for adaptive management applications and supports bioassessment and criteria development. It is a robust assessment tool that could be used to establish ecosystem condition that would aid resource managers in evaluating and communicating current or changing conditions, protect water and habitat quality in areas of high biological integrity, or develop restoration goals with stakeholders and other public beneficiaries.

Ecological Indicators↗
USGS2011

A heuristic simulation model of Lake Ontario circulation and mass balance transport

The redistribution of suspended organisms and materials by large-scale currents is part of natural ecological processes in large aquatic systems but can contribute to ecosystem disruption when exotic elements are introduced into the system. Toxic compounds and planktonic organisms spend various lengths of time in suspension before settling to the bottom or otherwise being removed. We constructed a simple physical simulation model, including the influence of major tributaries, to qualitatively examine circulation patterns in Lake Ontario. We used a simple mass balance approach to estimate the relative water input to and export from each of 10 depth regime-specific compartments (nearshore vs. offshore) comprising Lake Ontario. Despite its simplicity, our model produced circulation patterns similar to those reported by more complex studies in the literature. A three-gyre pattern, with the classic large counterclockwise central lake circulation, and a simpler two-gyre system were both observed. These qualitative simulations indicate little offshore transport along the south shore, except near the mouths of the Niagara River and Oswego River. Complex flow structure was evident, particularly near the Niagara River mouth and in offshore waters of the eastern basin. Average Lake Ontario residence time is 8 years, but the fastest model pathway indicated potential transport of plankton through the lake in as little as 60 days. This simulation illustrates potential invasion pathways and provides rough estimates of planktonic larval dispersal or chemical transport among nearshore and offshore areas of Lake Ontario. ?? 2011 Taylor & Francis.

Journal of Freshwater Ecology↗