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At least 109 records · Page 6Linked to original sources
USGS2022

Scale dependence of coral reef oases and their environmental correlates

Identifying relatively intact areas within ecosystems and determining the conditions favoring their existence is necessary for effective management in the context of widespread environmental degradation. In this study, we used 3766 surveys of randomly selected sites in the United States and U.S. Territories to identify the correlates of sites categorized as “oases” (defined as sites with relatively high total coral cover). We used occupancy models to evaluate the influence of 10 environmental predictors on the probability that an area (21.2-km 2 cell) would harbor coral oases defined at four spatial extents: cross-basin, basin, region, and subregion. Across all four spatial extents, oases were more likely to occur in habitats with high light attenuation. The influence of the other environmental predictors on the probability of oasis occurrence were less consistent and varied with the scale of observation. Oases were most likely in areas of low human population density, but this effect was evident only at the cross-basin and subregional extents. At the regional and subregional extents oases were more likely where sea-surface temperature was more variable, whereas at the larger spatial extents the opposite was true. By identifying the correlates of oasis occurrence, the model can inform the prioritization of reef areas for management. Areas with biophysical conditions that confer corals with physiological resilience, as well as limited human impacts, likely support coral reef oases across spatial extents. Our approach is widely applicable to the development of conservation strategies to protect biodiversity and ecosystems in an era of magnified human disturbance.

Ecological Applications↗
USGS1999

Characterizing fish community diversity across Virginia landscapes: Prerequisite for conservation

The number of community types occurring within landscapes is an important, but often unprotected, component of biological diversity. Generally applicable protocols for characterizing community diversity need to be developed to facilitate conservation. We used several multivariate techniques to analyze geographic variation in the composition of fish communities in Virginia streams. We examined relationships between community composition and six landscape variables: drainage basin, physiography, stream order, elevation, channel slope, and map coordinates. We compared patterns at two scales (statewide and subdrainage-specific) to assess sensitivity of community classification to spatial scale. We also compared patterns based on characterizing communities by species composition vs. ecological composition. All landscape variables explained significant proportions of the variance in community composition. Statewide, they explained 32% of the variance in species composition and 48% of the variance in ecological composition. Typical communities in each drainage or physiography were statistically distinctive. Communities in different combinations of drainage, physiography, and stream size were even more distinctive, but composition was strongly spatially autocorrelated. Ecological similarity and species similarity of community pairs were strongly related, but replacement by ecologically similar species was common among drainage–physiography combinations. Landscape variables explained significant proportions of variance in community composition within selected subdrainages, but proportions were less than at the statewide scale, and the explanatory power of individual variables varied considerably among subdrainages. Community variation within subdrainages appeared to be much more closely related to environmental variation than to replacement among ecologically similar species. Our results suggest that taxonomic and ecological characterizations of community composition are complementary; both are useful in a conservation context. Landscape features such as drainage, physiography, and water body size generally may provide a basis for assessing aquatic community diversity, especially in regions where the biota is poorly known. Systematic conservation of community types would be a major advance relative to most current conservation programs, which typically focus narrowly on populations of imperiled species. More effective conservation of aquatic biodiversity will require new approaches that recognize the value of both species and assemblages, and that emphasize protection of key landscape-scale processes.

Ecological Applications↗
USGS2018

Making do with less: Must sparse data preclude informed harvest strategies for European waterbirds?

The demography of many European waterbirds is not well understood because most countries have conducted little monitoring and assessment, and coordination among countries on waterbird management has little precedent. Yet intergovernmental treaties now mandate the use of sustainable, adaptive harvest strategies, whose development is challenged by a paucity of demographic information. In this study, we explore how a combination of allometric relationships, fragmentary monitoring and research information, and expert judgment can be used to estimate the parameters of a theta-logistic population model, which in turn can be used in a Markov decision process to derive optimal harvesting strategies. We show how to account for considerable parametric uncertainty, as well as for different management objectives. We illustrate our methodology with a poorly understood population of taiga bean geese ( Anser fabalis fabalis ), which is a popular game bird in Fennoscandia. Our results for taiga bean geese suggest that they may have demographic rates similar to other, well-studied species of geese, and our model-based predictions of population size are consistent with the limited monitoring information available. Importantly, we found that by using a Markov decision process, a simple scalar population model may be sufficient to guide harvest management of this species, even if its demography is age-structured. Finally, we demonstrated how two different management objectives can lead to very different optimal harvesting strategies, and how conflicting objectives may be traded off with each other. This approach will have broad application for European waterbirds by providing preliminary estimates of key demographic parameters, by providing insights into the monitoring and research activities needed to corroborate those estimates, and by producing harvest management strategies that are optimal with respect to the managers’ objectives, options, and available demographic information.

Ecological Applications↗
USGS2004

A hierarchical spatial model of avian abundance with application to Cerulean Warblers

Surveys collecting count data are the primary means by which abundance is indexed for birds. These counts are confounded, however, by nuisance effects including observer effects and spatial correlation between counts. Current methods poorly accommodate both observer and spatial effects because modeling these spatially autocorrelated counts within a hierarchical framework is not practical using standard statistical approaches. We propose a Bayesian approach to this problem and provide as an example of its implementation a spatial model of predicted abundance for the Cerulean Warbler (Dendroica cerulea) in the Prairie-Hardwood Transition of the upper midwestern United States. We used an overdispersed Poisson regression with fixed and random effects, fitted by Markov chain Monte Carlo methods. We used 21 years of North American Breeding Bird Survey counts as the response in a loglinear function of explanatory variables describing habitat, spatial relatedness, year effects, and observer effects. The model included a conditional autoregressive term representing potential correlation between adjacent route counts. Categories of explanatory habitat variables in the model included land cover composition and configuration, climate, terrain heterogeneity, and human influence. The inherent hierarchy in the model was from counts occurring, in part, as a function of observers within survey routes within years. We found that the percentage of forested wetlands, an index of wetness potential, and an interaction between mean annual precipitation and deciduous forest patch size best described Cerulean Warbler abundance. Based on a map of relative abundance derived from the posterior parameter estimates, we estimated that only 15% of the species' population occurred on federal land, necessitating active engagement of public landowners and state agencies in the conservation of the breeding habitat for this species. Models of this type can be applied to any data in which the response is counts, such as animal counts, activity (e.g.,nest) counts, or species richness. The most noteworthy practical application of this spatial modeling approach is the ability to map relative species abundance. The functional relationships that we elucidated for the Cerulean Warbler provide a basis for the development of management programs and may serve to focus management and monitoring on areas and habitat variables important to Cerulean Warblers.

Ecological Applications↗
USGS2012

Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models

Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus , the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species–energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients. Despite its common status, M. lucifugus was only detected during ∼50% of the surveys in occupied sample units. The overall naïve estimate for the proportion of the study region occupied by the species was 0.69, but after accounting for imperfect detection, this increased to ∼0.90. Our models provide evidence of an association between NPP and forest cover and M. lucifugus distribution, with implications for the projected effects of accelerated climate change in the region, which include net aridification as snowpack and stream flows decline. Annual turnover, the probability that an occupied sample unit was a newly occupied one, was estimated to be low (∼0.04–0.14), resulting in flat trend estimated with relatively high precision (SD = 0.04). We mapped the variation in predicted occurrence probabilities and corresponding prediction uncertainty along the productivity gradient. Our results provide a much needed baseline against which future anticipated declines in M. lucifugus occurrence can be measured. The dynamic distribution modeling approach has broad applicability to regional bat monitoring efforts now underway in several countries and we suggest ways to improve and expand our grid-based monitoring program to gain robust insights into bat population status and trend across large portions of North America.

Ecological Applications↗
USGS2011

Predicting phenology by integrating ecology, evolution and climate science

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology – the timing of life‐history events. Phenology has well‐demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species’ reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

Global Change Biology↗
USGS2013

Hydrogeomorphology explains acidification-driven variation in aquatic biological communities in the Neversink Basin, USA

Describing the distribution of aquatic habitats and the health of biological communities can be costly and time-consuming; therefore, simple, inexpensive methods to scale observations of aquatic biota to watersheds that lack data would be useful. In this study, we explored the potential of a simple “hydrogeomorphic” model to predict the effects of acid deposition on macroinvertebrate, fish, and diatom communities in 28 sub-watersheds of the 176-km 2 Neversink River basin in the Catskill Mountains of New York State. The empirical model was originally developed to predict stream-water acid neutralizing capacity (ANC) using the watershed slope and drainage density. Because ANC is known to be strongly related to aquatic biological communities in the Neversink, we speculated that the model might correlate well with biotic indicators of ANC response. The hydrogeomorphic model was strongly correlated to several measures of macroinvertebrate and fish community richness and density, but less strongly correlated to diatom acid tolerance. The model was also strongly correlated to biological communities in 18 sub-watersheds independent of the model development, with the linear correlation capturing the strongly acidic nature of small upland watersheds (<1 km 2 ). Overall, we demonstrated the applicability of geospatial data sets and a simple hydrogeomorphic model for estimating aquatic biological communities in areas with stream-water acidification, allowing estimates where no direct field observations are available. Similar modeling approaches have the potential to complement or refine expensive and time-consuming measurements of aquatic biota populations and to aid in regional assessments of aquatic health.

New York↗
USGS2019

Spatially explicit network analysis reveals multi-species annual cycle movement patterns of sea ducks

Conservation of long-distance migratory species poses unique challenges. Migratory connectivity—that is, the extent to which groupings of individuals at breeding sites are maintained in wintering areas—is frequently used to evaluate population structure and assess use of key habitat areas. However, for species with complex or variable annual-cycle movements, this traditional bimodal framework of migratory connectivity may be overly simplistic. Like many other waterfowl, sea ducks often travel to specific pre- and post-breeding sites outside their nesting and wintering areas to prepare for migration and, in some cases, molt their flight feathers. These additional molt migrations may play a key role in population structure, but are not included in traditional models of migratory connectivity. Network analysis, which applies graph theory to assess landscape connectivity, offers a powerful tool for quantitatively assessing the contributions of different sites used throughout the annual cycle to complex spatial networks. We collected satellite telemetry data on annual cycle movements of over 500 individual sea ducks of five species from throughout eastern North America and the Great Lakes. From these data, we constructed a multi-species network model of migratory patterns and site use over the course of the breeding, molting, wintering, and migration periods. Our results highlight inter- and intra-specific differences in the patterns and complexity of annual-cycle movement patterns, including the central importance of staging and molting sites in James Bay and the St. Lawrence River to multi-species habitat connectivity. We also discuss potential applications of network migration models to conservation prioritization, identification of population units, and integrating different data streams.

Ecological Applications↗
USGS2011

Past and ongoing shifts in Joshua tree distribution support future modeled range contraction

The future distribution of the Joshua tree (Yucca brevifolia) is projected by combining a geostatistical analysis of 20th-century climates over its current range, future modeled climates, and paleoecological data showing its response to a past similar climate change. As climate rapidly warmed ;11 700 years ago, the range of Joshua tree contracted, leaving only the populations near what had been its northernmost limit. Its ability to spread northward into new suitable habitats after this time may have been inhibited by the somewhat earlier extinction of megafaunal dispersers, especially the Shasta ground sloth. We applied a model of climate suitability for Joshua tree, developed from its 20th-century range and climates, to future climates modeled through a set of six individual general circulation models (GCM) and one suite of 22 models for the late 21st century. All distribution data, observed climate data, and future GCM results were scaled to spatial grids of ;1 km and ;4 km in order to facilitate application within this topographically complex region. All of the models project the future elimination of Joshua tree throughout most of the southern portions of its current range. Although estimates of future monthly precipitation differ between the models, these changes are outweighed by large increases in temperature common to all the models. Only a few populations within the current range are predicted to be sustainable. Several models project significant potential future expansion into new areas beyond the current range, but the species' Historical and current rates of dispersal would seem to prevent natural expansion into these new areas. Several areas are predicted to be potential sites for relocation/ assisted migration. This project demonstrates how information from paleoecology and modern ecology can be integrated in order to understand ongoing processes and future distributions.

Ecological Applications↗
USGS2022

Integrating growth and survival models for flexible estimation of size-dependent survival in a cryptic, endangered snake

Estimates of demographic rates for animal populations and individuals have many applications for ecological and conservation research. In many animals, survival is size-dependent, but estimating the form of the size–survival relationship presents challenges. For elusive species with low recapture rates, individuals’ size will be unknown at many points in time. Integrating growth and capture–mark–recapture models in a Bayesian framework empowers researchers to impute missing size data, with uncertainty, and include size as a covariate of survival, capture probability, and presence on-site. If there is no theoretical expectation for the shape of the size–survival relationship, spline functions can allow for fitting flexible, data-driven estimates. We use long-term capture–mark–recapture data from the endangered San Francisco gartersnake ( Thamnophis sirtalis tetrataenia ) to fit an integrated growth–survival model. Growth models showed that females reach longer asymptotic lengths than males and that the magnitude of sexual size dimorphism differed among populations. The capture probability and availability of San Francisco gartersnakes for capture increased with snout–vent length. The survival rate of female snakes exhibits a nonlinear relationship with snout–vent length (SVL), with survival flat between 300 mm and 550 mm SVL before decreasing for females between 550 mm and 700 mm SVL. For male snakes, survival decreased for adult males >550 mm SVL. The survival rates of the smallest and largest San Francisco gartersnakes were highly uncertain because recapture rates were very low for these sizes. By integrating growth and survival models and using penalized splines, we found support for size-dependent survival in San Francisco gartersnakes. Our results have applications for devising management activities for this endangered subspecies, and our methods could be applied broadly to the study of size-dependent demography among animals.

California↗
USGS2014

Barcodes are a useful tool for labeling and tracking ecological samples

Barcodes are used to label and track just about everything these days. Look around your office, in your medicine cabinet, at the package you just received in the mail, or on the shelves of any shop in town, and you will immediately grasp the ubiquity of their use. Interestingly, railroads and supermarkets were the early pioneers of barcode development: the former needing a way to track railway car location and ownership on a national scale, the latter needing a way to track a diverse array of products and to decrease checkout times (Nelson 1997). Barcodes first came to use in the sciences via the field of medicine, and the medical literature contains hundreds of publications describing how this technology has reduced errors in patient specimen identification and handling, where error mitigation is crucial. In short, barcodes have been adopted by many industries, and in many fields they are now synonymous with asset tracking. In spite of their potential to efficiently organize “assets” (i.e., samples) and minimize human error, the use of barcodes has yet to gain widespread application in ecology. In an age where students take notes on laptops instead of paper, and where “text messaging” involves a smartphone rather than a ball‐point pen, why do otherwise tech‐savvy ecologists persist in hand‐labeling samples? Why do we repeatedly transcribe long and unique identifiers at each step in the process of sample analysis, thereby wasting time and creating opportunities for transcription errors and data loss? Why are most sample storage areas only successfully navigable by the lab manager who personally shelved the samples? In the case of our large ecology lab—and, we suspect, in many others as well—the answer to these questions was perpetually, “bar‐coding won't be worth the trouble.” Recently, however, we realized this was no longer a sufficient answer when we started a new research project that involved collecting an additional thousands of samples each year; we decided to embrace the tangible benefits of an electronic labeling system, and implemented barcoding in our lab. To be clear, the use of barcoding in ecology is not completely novel, and there have been early adopters of this technology. For example, the Cedar Creek Long Term Ecological Research (LTER) site has been using barcodes since at least the mid‐1990s to track the large number of samples collected in their long‐term experimental grasslands (T. A. Kennedy, personal observation ). Overall, however, Cedar Creek is an outlier: in informal e‐mail surveys of LTER sites, only two of eight respondents used barcodes for sample identification or tracking, and even then their use was generally limited to certain samples or certain stages of sample analysis. Our objective in this article is to use our lab as a case study to highlight the potential of barcodes to simplify numerous aspects of sample collection and processing.

Arizona↗
USGS2011

Estimating equivalence with quantile regression

Equivalence testing and corresponding confidence interval estimates are used to provide more enlightened statistical statements about parameter estimates by relating them to intervals of effect sizes deemed to be of scientific or practical importance rather than just to an effect size of zero. Equivalence tests and confidence interval estimates are based on a null hypothesis that a parameter estimate is either outside (inequivalence hypothesis) or inside (equivalence hypothesis) an equivalence region, depending on the question of interest and assignment of risk. The former approach, often referred to as bioequivalence testing, is often used in regulatory settings because it reverses the burden of proof compared to a standard test of significance, following a precautionary principle for environmental protection. Unfortunately, many applications of equivalence testing focus on establishing average equivalence by estimating differences in means of distributions that do not have homogeneous variances. I discuss how to compare equivalence across quantiles of distributions using confidence intervals on quantile regression estimates that detect differences in heterogeneous distributions missed by focusing on means. I used one-tailed confidence intervals based on inequivalence hypotheses in a two-group treatment-control design for estimating bioequivalence of arsenic concentrations in soils at an old ammunition testing site and bioequivalence of vegetation biomass at a reclaimed mining site. Two-tailed confidence intervals based both on inequivalence and equivalence hypotheses were used to examine quantile equivalence for negligible trends over time for a continuous exponential model of amphibian abundance. ?? 2011 by the Ecological Society of America.

Ecological Applications↗
USGS1996

Concordance of seabird population parameters: Analytical methods and interpretation

In an ecological context, concordance may be defined as the tendency for paired values of some parameter, such as the annual productivity of bird species, to show similar directions and magnitudes of deviation from the mean. Where concordance among populations is high, there is an implied similarity of the ecological factors affecting performance. Conversely, if populations behave discordantly, dissimilarity of underlying ecological factors is likely. In evaluating birds as indicators of the marine environment, the biologist typically is confronted with a three-dimensional array of observations (species, areas, and years) in which there are more missing values than filled cells. This frustrates attempts to analyze concordance using existing methods (e.g., Kendall's coefficient, or correlation combined with cluster analysis), which are either impossible to apply to incomplete data sets or potentially misleading when applied to incomplete data sets. I suggest an alternative method for analyzing concordance that makes maximal use of available data. For a given data set partitioned into the smallest units containing information about concordance, one computes an index of concordance using a regression approach and tests for significance using randomization methods. This procedure would seem to have wide application to ecological studies generally and to seabird monitoring in particular.

Conference Paper↗
USGS2007

Stream ecosystem response to limestone treatment in acid impacted watersheds of the allegheny plateau

Restoration programs are expanding worldwide, but assessments of restoration effectiveness are rare. The objectives of our study were to assess current acid-precipitation remediation programs in streams of the Allegheny Plateau ecoregion of West Virginia (USA), identify specific attributes that could and could not be fully restored, and quantify temporal trends in ecosystem recovery. We sampled water chemistry, physical habitat, periphyton biomass, and benthic macroinvertebrate and fish community structure in three stream types: acidic (four streams), naturally circumneutral (eight streams), and acidic streams treated with limestone sand (eight streams). We observed no temporal trends in ecosystem recovery in treated streams despite sampling streams that ranged from 2 to 20 years since initial treatment. Our results indicated that the application of limestone sand to acidic streams was effective in fully recovering some characteristics, such as pH, alkalinity, Ca2+, Ca:H ratios, trout biomass and density, and trout reproductive success. However, recovery of many other characteristics was strongly dependent upon spatial proximity to treatment, and still others were never fully recovered. For example, limestone treatment did not restore dissolved aluminum concentrations, macroinvertebrate taxon richness, and total fish biomass to circumneutral reference conditions. Full recovery may not be occurring because treated streams continue to drain acidic watersheds and remain isolated in a network of acidic streams. We propose a revised stream restoration plan for the Allegheny Plateau that includes restoring stream ecosystems as connected networks rather than isolated reaches and recognizes that full recovery of acidified watersheds may not be possible. ?? 2007 by the Ecological Society of America.

Ecological Applications↗
USGS2022

Age-specific survival rates, causes of death, and allowable take of golden eagles in the western United States

In the United States, the Bald and Golden Eagle Protection Act prohibits take of golden eagles ( Aquila chrysaetos ) unless authorized by permit, and stipulates that all permitted take must be sustainable. Golden eagles are unintentionally killed in conjunction with many lawful activities (e.g., electrocution on power poles, collision with wind turbines). Managers who issue permits for incidental take of golden eagles must determine allowable take levels and manage permitted take accordingly. To aid managers in making these decisions in the western United States, we used an integrated population model to obtain estimates of golden eagle vital rates and population size, and then used those estimates in a prescribed take level (PTL) model to estimate the allowable take level. Estimated mean annual survival rates for golden eagles ranged from 0.70 (95% credible interval = 0.66–0.74) for first-year birds to 0.90 (0.88–0.91) for adults. Models suggested a high proportion of adult female golden eagles attempted to breed and breeding pairs fledged a mean of 0.53 (0.39–0.72) young annually. Population size in the coterminous western United States has averaged ~31,800 individuals for several decades, with λ = 1.0 (0.96–1.05). The PTL model estimated a median allowable take limit of ~2227 (708–4182) individuals annually given a management objective of maintaining a stable population. We estimate that take averaged 2572 out of 4373 (59%) deaths annually, based on a representative sample of transmitter-tagged golden eagles. For the subset of golden eagles that were recovered and a cause of death determined, anthropogenic mortality accounted for an average of 74% of deaths after their first year; leading forms of take over all age classes were shooting (~670 per year), collisions (~611), electrocutions (~506), and poisoning (~427). Although observed take overlapped the credible interval of our allowable take estimate and the population overall has been stable, our findings indicate that additional take, unless mitigated for, may not be sustainable. Our analysis demonstrates the utility of the joint application of integrated population and prescribed take level models to management of incidental take of a protected species.

western United States↗
USGS1998

Population models of burrowing mayfly recolonization in western Lake Erie

Burrowing mayflies, Hexagenia spp. ( H. limbata and H. rigida ), began recolonizing western Lake Erie during the 1990s. Survey data for mayfly nymph densities indicated that the population experienced exponential growth between 1991 and 1997. To predict the time to full recovery of the mayfly population, we fitted logistic models, ranging in carrying capacity from 600 to 2000 nymphs/m 2 , to these survey data. Based on the fitted logistic curves, we forecast that the mayfly population in western Lake Erie would achieve full recovery between years 1998 and 2000, depending on the carrying capacity of the western basin. Additionally, we estimated the mortality rate of nymphs in western Lake Erie during 1994 and then applied an age-based matrix model to the mayfly population. The results of the matrix population modeling corroborated the exponential growth model application in that both methods yielded an estimate of the population growth rate, r, in excess of 0.8 yr −1 . This was the first evidence that mayfly populations are capable of recolonizing large aquatic ecosystems at rates comparable with those observed in much smaller lentic ecosystems. Our model predictions should prove valuable to managers of power plant facilities along the western basin in planning for mayfly emergences and to managers of the yellow perch ( Perca flavescens ) fishery in western Lake Erie.

Michigan, Ohio, Ontario↗
USGS2017

Standardization and application of an index of community integrity for waterbirds in the Chesapeake Bay, USA

In recent decades, there has been increasing interest in the application of ecological indices to assess ecosystem condition in response to anthropogenic activities. An Index of Waterbird Community Integrity was previously developed for the Chesapeake Bay, USA. However, the scoring criteria were not defined well enough to generate scores for new species that were not observed in the original study. The goal of this study was to explicitly define the scoring criteria for the existing index and to develop index scores for all waterbirds of the Chesapeake Bay. The standardized index then was applied to a case study investigating the relationship between waterbird community integrity and shoreline development during late summer and late fall (2012–2014) using an alternative approach to survey methodology, which allowed for greater area coverage compared to the approach used in the original study. Index scores for both seasons were negatively related to percentage of developed shorelines. Providing these updated tools using the detailed scoring system will facilitate future application to new species or development of the index in other estuaries worldwide. This methodology allows for consistent cross-study comparisons and can be combined with other community integrity indices, allowing for more effective estuarine management.

Chesapeake Bay↗
USGS2007

Forest dynamics in Oregon landscapes: Evaluation and application of an individual-based model

The FORCLIM model of forest dynamics was tested against field survey data for its ability to simulate basal area and composition of old forests across broad climatic gradients in western Oregon, USA. The model was also tested for its ability to capture successional trends in ecoregions of the west Cascade Range. It was then applied to simulate present and future (1990-2050) forest landscape dynamics of a watershed in the west Cascades. Various regimes of climate change and harvesting in the watershed were considered in the landscape application. The model was able to capture much of the variation in forest basal area and composition in western Oregon even though temperature and precipitation were the only inputs that were varied among simulated sites. The measured decline in total basal area from tall coastal forests eastward to interior steppe was matched by simulations. Changes in simulated forest dominants also approximated those in the actual data. Simulated abundances of a few minor species did not match actual abundances, however. Subsequent projections of climate change and harvest effects in a west Cascades landscape indicated no change in forest dominance as of 2050. Yet, climate-driven shifts in the distributions of some species were projected. The simulation of both stand-replacing and partial-stand disturbances across western Oregon improved agreement between simulated and actual data. Simulations with fire as an agent of partial disturbance suggested that frequent fires of low severity can alter forest composition and structure as much or more than severe fires at historic frequencies. ?? 2007 by the Ecological Society of America.

Ecological Applications↗