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USGS2003

Small-mammal density estimation: A field comparison of grid-based vs. web-based density estimators

Statistical models for estimating absolute densities of field populations of animals have been widely used over the last century in both scientific studies and wildlife management programs. To date, two general classes of density estimation models have been developed: models that use data sets from capture–recapture or removal sampling techniques (often derived from trapping grids) from which separate estimates of population size ( NÌ‚ ) and effective sampling area ( AÌ‚ ) are used to calculate density ( DÌ‚ = NÌ‚ / AÌ‚ ); and models applicable to sampling regimes using distance-sampling theory (typically transect lines or trapping webs) to estimate detection functions and densities directly from the distance data. However, few studies have evaluated these respective models for accuracy, precision, and bias on known field populations, and no studies have been conducted that compare the two approaches under controlled field conditions. In this study, we evaluated both classes of density estimators on known densities of enclosed rodent populations. Test data sets ( n = 11) were developed using nine rodent species from capture–recapture live-trapping on both trapping grids and trapping webs in four replicate 4.2-ha enclosures on the Sevilleta National Wildlife Refuge in central New Mexico, USA. Additional “saturation” trapping efforts resulted in an enumeration of the rodent populations in each enclosure, allowing the computation of true densities. Density estimates ( DÌ‚ ) were calculated using program CAPTURE for the grid data sets and program DISTANCE for the web data sets, and these results were compared to the known true densities ( D ) to evaluate each model's relative mean square error, accuracy, precision, and bias. In addition, we evaluated a variety of approaches to each data set's analysis by having a group of independent expert analysts calculate their best density estimates without a priori knowledge of the true densities; this “blind” test allowed us to evaluate the influence of expertise and experience in calculating density estimates in comparison to simply using default values in programs CAPTURE and DISTANCE. While the rodent sample sizes were considerably smaller than the recommended minimum for good model results, we found that several models performed well empirically, including the web-based uniform and half-normal models in program DISTANCE, and the grid-based models M b and M bh in program CAPTURE (with AÌ‚ adjusted by species-specific full mean maximum distance moved (MMDM) values). These models produced accurate DÌ‚ values (with 95% confidence intervals that included the true D values) and exhibited acceptable bias but poor precision. However, in linear regression analyses comparing each model's DÌ‚ values to the true D values over the range of observed test densities, only the web-based uniform model exhibited a regression slope near 1.0; all other models showed substantial slope deviations, indicating biased estimates at higher or lower density values. In addition, the grid-based DÌ‚ analyses using full MMDM values for WÌ‚ area adjustments required a number of theoretical assumptions of uncertain validity, and we therefore viewed their empirical successes with caution. Finally, density estimates from the independent analysts were highly variable, but estimates from web-based approaches had smaller mean square errors and better achieved confidence-interval coverage of D than did grid-based approaches. Our results support the contention that web-based approaches for density estimation of small-mammal populations are both theoretically and empirically superior to grid-based approaches, even when sample size is far less than often recommended. In view of the increasing need for standardized environmental measures for comparisons among ecosystems and through time, analytical models based on distance sampling appear to offer accurate density estimation approaches for research studies involving small-mammal abundances.

Ecological Monographs↗

USGS2006

Response of Everglades tree islands to environmental change

Tree islands are centers of biodiversity within the Florida Everglades, USA, but the factors controlling their distribution, formation, and development are poorly understood. We use pollen assemblages from tree islands throughout the greater Everglades ecosystem to reconstruct the timing of tree island formation, patterns of development, and response to specific climatic and environmental stressors. These data indicate that fixed (teardrop-shaped) and strand tree islands developed well before substantial human alteration of the system, with initial tree island vegetation in place between 3500 and 500 calibrated years before present (cal yr BP), depending on the location in the Everglades wetland. Tree island development appears to have been triggered by regional- to global-scale climatic events at 2800 cal yr BP, 1600–1500 cal yr BP, 1200–1000 cal yr BP (early Medieval Warm Period), and 500–200 cal yr BP (Little Ice Age). These periods correspond to drought intervals documented in Central and South America and periods of southward displacement of the Intertropical Convergence Zone. The records indicate a coherence of climate patterns in both subtropical North America and the Northern Hemisphere Neotropics. Water management practices of the 20th century altered plant communities and size of tree islands throughout the Everglades. Responses range from loss of tree islands due to artificially long hydroperiods and deep water to expansion of tree islands after flow reductions. These data provide evidence for the rapidity of tree island response to specific hydrologic change and facilitate prediction of the response to future changes associated with Everglades restoration plans.

Florida↗

USGS2004

Determinants of reproductive costs in the long-lived Black-legged Kittiwake: A multiyear experiment

We studied reproductive costs of Black-legged Kittiwakes ( Rissa tridactyla ) in Prince William Sound, Alaska (USA) by removing entire clutches from randomly selected nests over four successive years, and then contrasting survival and fecundity of adults from manipulated and unmanipulated nests in each subsequent year. To elucidate mechanisms that lead to the expression of reproductive costs, we simultaneously characterized several behavioral and physiological parameters among adults in the two treatment groups. We also examined naturally nonbreeding adults that previously bred to determine their survival and future nonbreeding probabilities. Food availability varied during the study, being generally poor at the onset, and improving in later years. Adult nest attendance and body condition (assessed late in the chick- rearing period) varied accordingly among years, and between adults raising chicks and adults that had their eggs removed. Adults from unmanipulated nests incurred significant survival costs in all years, although fecundity costs were strongly expressed in only one of four years. Neither survival nor fecundity costs were strongly influenced by body condition or food availability, and no difference in reproductive costs was detected between the sexes. Although unmanipulated breeders survived at lower rates than manipulated breeders due to costs of reproduction, their survival rates were elevated compared to those of natural nonbreeders, presumably due to differences in individual ability. These findings indicate that models of adult survival must consider not only an organism's reproductive state, but also the factors that lead to that state. Although body condition appeared to be weakly related to survival, it was insufficient to explain the full magnitude of survival costs observed. We suggest that other parameters that were found to differ between treatment groups (e.g., rates of energy turnover, baseline levels of stress, and patterns of allocating body reserves) may be important mechanistic determinants of reproductive costs in kittiwakes, and potentially other long-lived species. Future efforts should move beyond simple assessments of body condition and toward more integrated measures of physiological condition when attempting to identify factors that influence how long-lived species balance the costs and benefits of reproduction.

Alaska↗

USGS2004

Geographic structure of adelie penguin populations: overlap in colony-specific foraging areas

In an investigation of the factors leading to geographic structuring among Ade??lie Penguin (Pygoscelis adeliae) populations, we studied the size and overlap of colony-specific foraging areas within an isolated cluster of colonies. The study area, in the southwestern Ross Sea, included one large and three smaller colonies, ranging in size from 3900 to 135000 nesting pairs, clustered on Ross and Beaufort Islands. We used triangulation of radio signals from transmitters attached to breeding penguins to determine foraging locations and to define colony-specific foraging areas during the chick-provisioning period of four breeding seasons, 1997-2000. Colony populations (nesting pairs) were determined using aerial photography just after egg-laying; reproductive success was estimated by comparing ground counts of chicks fledged to the number of breeding pairs apparent in aerial photos. Foraging-trip duration, meal size, and adult body mass were estimated using RFID (radio frequency identification) tags and an automated reader and weighbridge. Chick growth was assessed by weekly weighing. We related the following variables to colony size: foraging distance, area, and duration; reproductive success; chick meal size and growth rate; and seasonal variation in adult body mass. We found that penguins foraged closest to their respective colonies, particularly at the smaller colonies. However, as the season progressed, foraging distance, duration, and area increased noticeably, especially at the largest colony. The foraging areas of the smaller colonies overlapped broadly, but very little foraging area overlap existed between the large colony and the smaller colonies, even though the foraging area of the large colony was well within range of the smaller colonies. Instead, the foraging areas of the smaller colonies shifted as that of the large colony grew. Colony size was not related to chick meal size, chick growth, or parental body mass. This differed from the year previous to the study, when foraging trips of the large colony were very long, parents lost mass, and chick meals were smaller. In light of existing data on prey abundance in neritic waters in Antarctica suggesting that krill are relatively evenly distributed and in high abundance in the Southern Ross Sea, we conclude that penguins depleted or changed the availability of their prey, that the degree of alteration was a function of colony size, and that the large colony affected the location (and perhaps ultimately the size) of foraging areas for the smaller colonies. It appears, therefore, that foraging dynamics play a role in the geographic structuring of colonies in this species. ?? 2004 by the Ecological Society of America.

Ecological Monographs↗

USGS2007

Hierarchical spatial models of abundance and occurrence from imperfect survey data

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

Ecological Monographs↗

USGS2009

Scaling the effects of moose browsing on forage distribution, from the geometry of plant canopies to landscapes

Landscape heterogeneity influences large herbivores by altering their feeding rates, but as herbivores attempt to maximize feeding rates they also create spatial heterogeneity by altering plant growth. Herbivore feeding rates thus provide a quantitative link between the causes and consequences of spatial heterogeneity in herbivore-dominated ecosystems. The fractal geometry of plant canopies determines both the density and mass of twigs available to foraging herbivores. These properties determine a threshold distance between plants (d * ) that distinguishes the mechanisms regulating herbivore intake rates. When d * is greater than the actual distance between plants (d), intake is regulated by the rate of food processing in the mouth. But when d * < d, intake is regulated by the rate at which the herbivore encounters new plants. Alterations to plant geometry due to past browsing could change the rate at which herbivores encounter and process bites of plant tissue, modify d * relative to d, and thus change intake rates and the distribution of mechanisms regulating it across landscapes. We measured changes in the geometry of aspen (Populus tremuloides) and balsam fir (Abies balsamea) saplings along gradients of moose browsing from 2001 to 2005 at Isle Royale National Park, Michigan, USA. For aspen saplings, fractal dimension of bite density, bite mass, and forage biomass responded quadratically to increasing moose browsing and were greatest at -3-4 g-g.m-2.yr" 1 consumption. For balsam fir, in contrast, these same measures declined steadily with increasing moose browsing. The different responses of plant canopies to increased browsing altered d * around plants. In summer, d * > d for aspen saplings at all prior consumption levels. Food processing therefore regulated summer moose feeding rates across our landscapes. In winter, changes in bite mass due to past browsing were sufficient to cause d * < d for aspen and balsam fir. Therefore, travel velocity and food processing jointly regulated intake rate during winter. Browsing-induced changes in the small-scale geometry of plant canopies can determine intake rate at larger spatial scales by changing d * relative to d and, hence, which mechanisms determine intake rate, essentially altering how herbivores sense the distribution of their food resources. ?? 2009 by the Ecological Society of America.

Ecological Monographs↗

USGS2009

Sensitivity of the carbon cycle in the Arctic to climate change

The recent warming in the Arctic is affecting a broad spectrum of physical, ecological, and human/cultural systems that may be irreversible on century time scales and have the potential to cause rapid changes in the earth system. The response of the carbon cycle of the Arctic to changes in climate is a major issue of global concern, yet there has not been a comprehensive review of the status of the contemporary carbon cycle of the Arctic and its response to climate change. This review is designed to clarify key uncertainties and vulnerabilities in the response of the carbon cycle of the Arctic to ongoing climatic change. While it is clear that there are substantial stocks of carbon in the Arctic, there are also significant uncertainties associated with the magnitude of organic matter stocks contained in permafrost and the storage of methane hydrates beneath both subterranean and submerged permafrost of the Arctic. In the context of the global carbon cycle, this review demonstrates that the Arctic plays an important role in the global dynamics of both CO 2 and CH 4 . Studies suggest that the Arctic has been a sink for atmospheric CO 2 of between 0 and 0.8 Pg C/yr in recent decades, which is between 0% and 25% of the global net land/ocean flux during the 1990s. The Arctic is a substantial source of CH 4 to the atmosphere (between 32 and 112 Tg CH 4 /yr), primarily because of the large area of wetlands throughout the region. Analyses to date indicate that the sensitivity of the carbon cycle of the Arctic during the remainder of the 21st century is highly uncertain. To improve the capability to assess the sensitivity of the carbon cycle of the Arctic to projected climate change, we recommend that (1) integrated regional studies be conducted to link observations of carbon dynamics to the processes that are likely to influence those dynamics, and (2) the understanding gained from these integrated studies be incorporated into both uncoupled and fully coupled carbon–climate modeling efforts.

Ecological Monographs↗

USGS2010

On the specification of structural equation models for ecological systems

The use of structural equation modeling (SEM) is often motivated by its utility for investigating complex networks of relationships, but also because of its promise as a means of representing theoretical concepts using latent variables. In this paper, we discuss characteristics of ecological theory and some of the challenges for proper specification of theoretical ideas in structural equation models (SE models). In our presentation, we describe some of the requirements for classical latent variable models in which observed variables (indicators) are interpreted as the effects of underlying causes. We also describe alternative model specifications in which indicators are interpreted as having causal influences on the theoretical concepts. We suggest that this latter nonclassical specification (which involves another variable type—the composite) will often be appropriate for ecological studies because of the multifaceted nature of our theoretical concepts. In this paper, we employ the use of meta‐models to aid the translation of theory into SE models and also to facilitate our ability to relate results back to our theories. We demonstrate our approach by showing how a synthetic theory of grassland biodiversity can be evaluated using SEM and data from a coastal grassland. In this example, the theory focuses on the responses of species richness to abiotic stress and disturbance, both directly and through intervening effects on community biomass. Models examined include both those based on classical forms (where each concept is represented using a single latent variable) and also ones in which the concepts are recognized to be multifaceted and modeled as such. To address the challenge of matching SE models with the conceptual level of our theory, two approaches are illustrated, compositing and aggregation. Both approaches are shown to have merits, with the former being preferable for cases where the multiple facets of a concept have widely differing effects in the system and the latter being preferable where facets act together consistently when influencing other parts of the system. Because ecological theory characteristically deals with concepts that are multifaceted, we expect the methods presented in this paper will be useful for ecologists wishing to use SEM.

Ecological Monographs↗

USGS2011

Causes and implications of the correlation between forest productivity and tree mortality rates

At global and regional scales, tree mortality rates are positively correlated with forest net primary productivity (NPP). Yet causes of the correlation are unknown, in spite of potentially profound implications for our understanding of environmental controls of forest structure and dynamics and, more generally, our understanding of broad-scale environmental controls of population dynamics and ecosystem processes. Here we seek to shed light on the causes of geographic patterns in tree mortality rates, and we consider some implications of the positive correlation between mortality rates and NPP. To reach these ends, we present seven hypotheses potentially explaining the correlation, develop an approach to help distinguish among the hypotheses, and apply the approach in a case study comparing a tropical and temperate forest. Based on our case study and literature synthesis, we conclude that no single mechanism controls geographic patterns of tree mortality rates. At least four different mechanisms may be at play, with the dominant mechanisms depending on whether the underlying productivity gradients are caused by climate or soil fertility. Two of the mechanisms are consequences of environmental selection for certain combinations of life-history traits, reflecting trade-offs between growth and defense (along edaphic productivity gradients) and between reproduction and persistence (as manifested in the adult tree stature continuum along climatic and edaphic gradients). The remaining two mechanisms are consequences of environmental influences on the nature and strength of ecological interactions: competition (along edaphic gradients) and pressure from plant enemies (along climatic gradients). For only one of these four mechanisms, competition, can high mortality rates be considered to be a relatively direct consequence of high NPP. The remaining mechanisms force us to adopt a different view of causality, in which tree growth rates and probability of mortality can vary with at least a degree of independence along productivity gradients. In many cases, rather than being a direct cause of high mortality rates, NPP may remain high in spite of high mortality rates. The independent influence of plant enemies and other factors helps explain why forest biomass can show little correlation, or even negative correlation, with forest NPP.

Ecological Monographs↗

USGS2011

Decomposition of heterogeneous organic matterand its long-term stabilization in soils

Soil organic matter is a complex mixture of material with heterogeneous biological, physical, and chemical properties. Decomposition models represent this heterogeneity either as a set of discrete pools with different residence times or as a continuum of qualities. It is unclear though, whether these two different approaches yield comparable predictions of organic matter dynamics. Here, we compare predictions from these two different approaches and propose an intermediate approach to study organic matter decomposition based on concepts from continuous models implemented numerically. We found that the disagreement between discrete and continuous approaches can be considerable depending on the degree of nonlinearity of the model and simulation time. The two approaches can diverge substantially for predicting long-term processes in soils. Based on our alternative approach, which is a modification of the continuous quality theory, we explored the temporal patterns that emerge by treating substrate heterogeneity explicitly. The analysis suggests that the pattern of carbon mineralization over time is highly dependent on the degree and form of nonlinearity in the model, mostly expressed as differences in microbial growth and efficiency for different substrates. Moreover, short-term stabilization and destabilization mechanisms operating simultaneously result in long-term accumulation of carbon characterized by low decomposition rates, independent of the characteristics of the incoming litter. We show that representation of heterogeneity in the decomposition process can lead to substantial improvements in our understanding of carbon mineralization and its long-term stability in soils.

Ecological Monographs↗

USGS2013

Food-web dynamics in a large river discontinuum

Nearly all ecosystems have been altered by human activities, and most communities are now composed of interacting species that have not co-evolved. These changes may modify species interactions, energy and material flows, and food-web stability. Although structural changes to ecosystems have been widely reported, few studies have linked such changes to dynamic food-web attributes and patterns of energy flow. Moreover, there have been few tests of food-web stability theory in highly disturbed and intensely managed freshwater ecosystems. Such synthetic approaches are needed for predicting the future trajectory of ecosystems, including how they may respond to natural or anthropogenic perturbations. We constructed flow food webs at six locations along a 386-km segment of the Colorado River in Grand Canyon (Arizona, USA) for three years. We characterized food-web structure and production, trophic basis of production, energy efficiencies, and interaction-strength distributions across a spatial gradient of perturbation (i.e., distance from Glen Canyon Dam), as well as before and after an experimental flood. We found strong longitudinal patterns in food-web characteristics that strongly correlated with the spatial position of large tributaries. Above tributaries, food webs were dominated by nonnative New Zealand mudsnails (62% of production) and nonnative rainbow trout (100% of fish production). The simple structure of these food webs led to few dominant energy pathways (diatoms to few invertebrate taxa to rainbow trout), large energy inefficiencies (i.e., <20% of invertebrate production consumed by fishes), and right-skewed interaction-strength distributions, consistent with theoretical instability. Below large tributaries, invertebrate production declined ∼18-fold, while fish production remained similar to upstream sites and comprised predominately native taxa (80–100% of production). Sites below large tributaries had increasingly reticulate and detritus-based food webs with a higher prevalence of omnivory, as well as interaction strength distributions more typical of theoretically stable food webs (i.e., nearly twofold higher proportion of weak interactions). Consistent with theory, downstream food webs were less responsive to the experimental flood than sites closest to the dam. We show how human-induced shifts to food-web structure can affect energy flow and interaction strengths, and we show that these changes have consequences for food-web function and response to perturbations.

Arizona↗

USGS2015

A guide to Bayesian model selection for ecologists

The steady upward trend in the use of model selection and Bayesian methods in ecological research has made it clear that both approaches to inference are important for modern analysis of models and data. However, in teaching Bayesian methods and in working with our research colleagues, we have noticed a general dissatisfaction with the available literature on Bayesian model selection and multimodel inference. Students and researchers new to Bayesian methods quickly find that the published advice on model selection is often preferential in its treatment of options for analysis, frequently advocating one particular method above others. The recent appearance of many articles and textbooks on Bayesian modeling has provided welcome background on relevant approaches to model selection in the Bayesian framework, but most of these are either very narrowly focused in scope or inaccessible to ecologists. Moreover, the methodological details of Bayesian model selection approaches are spread thinly throughout the literature, appearing in journals from many different fields. Our aim with this guide is to condense the large body of literature on Bayesian approaches to model selection and multimodel inference and present it specifically for quantitative ecologists as neutrally as possible. We also bring to light a few important and fundamental concepts relating directly to model selection that seem to have gone unnoticed in the ecological literature. Throughout, we provide only a minimal discussion of philosophy, preferring instead to examine the breadth of approaches as well as their practical advantages and disadvantages. This guide serves as a reference for ecologists using Bayesian methods, so that they can better understand their options and can make an informed choice that is best aligned with their goals for inference.

Ecological Monographs↗

USGS2015

Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts

Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal ( Phoca largha ) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total abundance produced estimates that largely conformed to our a priori expectation. Although care must be taken to tailor models to match the study population and survey data available, we argue that hierarchical spatiotemporal statistical models represent a powerful way forward for estimating abundance and explaining variation in the distribution of dynamical populations.

Ecological Monographs↗

USGS2015

State-space modeling to support management of brucellosis in the Yellowstone bison population

The bison ( Bison bison ) of the Yellowstone ecosystem, USA, exemplify the difficulty of conserving large mammals that migrate across the boundaries of conservation areas. Bison are infected with brucellosis ( Brucella abortus ) and their seasonal movements can expose livestock to infection. Yellowstone National Park has embarked on a program of adaptive management of bison, which requires a model that assimilates data to support management decisions. We constructed a Bayesian state-space model to reveal the influence of brucellosis on the Yellowstone bison population. A frequency-dependent model of brucellosis transmission was superior to a density-dependent model in predicting out-of-sample observations of horizontal transmission probability. A mixture model including both transmission mechanisms converged on frequency dependence. Conditional on the frequency-dependent model, brucellosis median transmission rate was 1.87 yr −1 . The median of the posterior distribution of the basic reproductive ratio ( R 0 ) was 1.75. Seroprevalence of adult females varied around 60% over two decades, but only 9.6 of 100 adult females were infectious. Brucellosis depressed recruitment; estimated population growth rate λ averaged 1.07 for an infected population and 1.11 for a healthy population. We used five-year forecasting to evaluate the ability of different actions to meet management goals relative to no action. Annually removing 200 seropositive female bison increased by 30-fold the probability of reducing seroprevalence below 40% and increased by a factor of 120 the probability of achieving a 50% reduction in transmission probability relative to no action. Annually vaccinating 200 seronegative animals increased the likelihood of a 50% reduction in transmission probability by fivefold over no action. However, including uncertainty in the ability to implement management by representing stochastic variation in the number of accessible bison dramatically reduced the probability of achieving goals using interventions relative to no action. Because the width of the posterior predictive distributions of future population states expands rapidly with increases in the forecast horizon, managers must accept high levels of uncertainty. These findings emphasize the necessity of iterative, adaptive management with relatively short-term commitment to action and frequent reevaluation in response to new data and model forecasts. We believe our approach has broad applications.

Wyoming↗

USGS2015

The ecology of methane in streams and rivers: Patterns, controls, and global significance

Streams and rivers can substantially modify organic carbon (OC) inputs from terrestrial landscapes, and much of this processing is the result of microbial respiration. While carbon dioxide (CO 2 ) is the major end-product of ecosystem respiration, methane (CH 4 ) is also present in many fluvial environments even though methanogenesis typically requires anoxic conditions that may be scarce in these systems. Given recent recognition of the pervasiveness of this greenhouse gas in streams and rivers, we synthesized existing research and data to identify patterns and drivers of CH 4 , knowledge gaps, and research opportunities. This included examining the history of lotic CH 4 research, creating a database of concentrations and fluxes (MethDB) to generate a global-scale estimate of fluvial CH 4 efflux, and developing a conceptual framework and using this framework to consider how human activities may modify fluvial CH 4 dynamics. Current understanding of CH 4 in streams and rivers has been strongly influenced by goals of understanding OC processing and quantifying the contribution of CH 4 to ecosystem C fluxes. Less effort has been directed towards investigating processes that dictate in situ CH 4 production and loss. CH 4 makes a meager contribution to watershed or landscape C budgets, but streams and rivers are often significant CH 4 sources to the atmosphere across these same spatial extents. Most fluvial systems are supersaturated with CH 4 and we estimate an annual global emission of 26.8 Tg CH 4 , equivalent to ~15-40% of wetland and lake effluxes, respectively. Less clear is the role of CH 4 oxidation, methanogenesis, and total anaerobic respiration to whole ecosystem production and respiration. Controls on CH 4 generation and persistence can be viewed in terms of proximate controls that influence methanogenesis (organic matter, temperature, alternative electron acceptors, nutrients) and distal geomorphic and hydrologic drivers. Multiple controls combined with its extreme redox status and low solubility result in high spatial and temporal variance of CH 4 in fluvial environments, which presents a substantial challenge for understanding its larger-scale dynamics. Further understanding of CH 4 production and consumption, anaerobic metabolism, and ecosystem energetics in streams and rivers can be achieved through more directed studies and comparison with knowledge from terrestrial, wetland, and aquatic disciplines.

Ecological Monographs↗

USGS2006

Population dynamics of Greater Scaup breeding on the Yukon-Kuskokwim Delta, Alaska

Populations of greater scaup ( Aythya marila ) remained relatively stable during a period when populations of lesser scaup ( A. affinis ) have declined from historic levels. To assist in describing these differences in population trends, from 1991 through 2000, we studied the survival, nesting ecology, and productivity of greater scaup on the Yukon-Kuskokwim Delta (Y-K Delta), Alaska, to develop a model of population dynamics. We located nests, radio-marked females for renesting studies, estimated duckling survival, and leg-banded females to examine nest site fidelity and annual survival. Greater scaup initiated egg laying later than other species, and most clutches (>80%) were initiated over 20 days each year. We located 1,056 nests; nest success ranged from 7 to 61 % among years. Following loss of their first clutch, 51 % of radio-tagged females attempted to renest. Duckling survival to 30 days of age was 37.5%. Our best model suggested that annual survival did not vary among years and averaged 81 %. Survival rate was positively related to structural body size. Only 8 of 214 banded individuals were reported as recovered (1 each in Maryland, Michigan, Minnesota, Washington, and Alaska and 3 in California). Using a stochastic model, we estimated that, on average, breeding females produced 0.57 young females/nesting season. We combined this estimate of productivity with our annual estimates of adult survival and an assumed population growth rate of 1.0, then solved for an estimate of first-year survival (0.40). Under these conditions the predicted stable age distribution of breeding females (i.e., the nesting population) was 15.1% 1-year-old, 4.1% 2-year-old first-time breeders, and 80.8% 2-year-old and older, experienced breeders. We subjected this stochastic model to perturbation analyses to examine the relative effects of demographic parameters on k. The relative effects of productivity and adult survival on the population growth rate were 0.26 and 0.72, respectively. Thus, compared to productivity, proportionally equivalent changes in annual survival would have 2.8 times the effect on k. However, when we examined annual variation in predicted population size using standardized regression coefficients, productivity explained twice as much variation as annual survival. Thus, management actions focused on changes in survival or productivity have the ability to influence population size; however, substantially larger changes in productivity are required to influence population trends.

Wildlife Monographs↗

USGS2006

Pathogens, nutritional deficiency, and climate influences on a declining moose population

Several potential proximate causes may be implicated in a recent (post-1984) decline in moose ( Alces alces andersoni ) numbers at their southern range periphery in northwest Minnesota, USA. These causes include deleterious effects of infectious pathogens, some of which are associated with white-tailed deer ( Odocoileus virginianus ), negative effects of climate change, increased food competition with deer or moose, legal or illegal hunting, and increased predation by gray wolves ( Canis lupus ) and black bears ( Ursus americanus ). Long-standing factors that may have contributed to the moose decline include those typically associated with marginal habitat such as nutritional deficiencies. We examined survival and productivity among radiocollared ( n = 152) adult female and juvenile moose in northwest Minnesota during 1995–2000, and assessed cause of death and pathology through carcass necropsy of radiocollared and non-radiocollared animals. Aerial moose surveys suggested that hunting was an unlikely source of the numerical decline because the level of harvest was relatively low (i.e., approx. 15% / 2 yr) and the population usually grew in years following a hunt. The majority of moose mortalities (up to 87% of radiocollared moose [ n = 76] and up to 65% of non-radiocollared moose [ n = 84]) were proximally related to pathology associated with parasites and infectious disease. Liver fluke ( Fascioloides magna ) infections apparently constituted the greatest single source of mortality and caused significant pathology in the liver, thoracic and peritoneal cavities, pericardial sac, and lungs. Mortality due to meningeal worm ( Parelaphostrongylus tenuis ) was less prevalent and was manifested through characteristic neurological disease. Several mortalities apparently were associated with unidentified infectious disease, probably acting in close association with malnutrition. Bone-marrow fat was lower for moose dying of natural causes than those dying of anthropogenic factors or accidents, implying that acute malnutrition contributed to moose mortality. Blood profiles from live-captured animals indicated that those dying in the subsequent 18 months were chronically malnourished. Relative to other populations, average annual survival rates for adult females (0.79 [0.74–0.84; 95% CI]) and yearlings (0.64 [0.48–0.86]) were low, whereas those for calves (0.66 [0.53–081]) were high. Pregnancy (48%) and twinning (19%) rates were among the lowest reported for moose, with reproductive senescence among females being apparent as early as 8 years. Pregnancy status was related to indices of acute (i.e., bone-marrow fat) and chronic (i.e., blood condition indices) malnutrition. Opportunistic carcass recovery indicated that there likely were few prime-aged males (>5 yr old) in the population. Analysis of protein content in moose browse and fecal samples indicated that food quality was probably adequate to support moose over winter, but the higher fecal protein among animals that died in the subsequent 18 months could be indicative of protein catabolism associated with malnutrition. Trace element analysis from moose livers revealed apparent deficiencies in copper and selenium, but there was limited evidence of direct association between trace element concentrations and moose disease, pathology, or mortality. Time-series analysis of regional moose counts (1961–2000) indicated that annual population growth rate was related negatively to mean summer temperature, with winter and summer temperatures increasing by an average of 6.8 and 2.1 C, respectively, during the 40-year period. This change may have increased moose thermoregulatory costs and disrupted their energy balance, and thereby reduced their fitness. Time-series analysis failed to show a relationship between annual population growth rate and moose or deer abundance, indicating that food limitation via resource competition was unlikely. Population viability analyses, using count data (1961–2000) and demographic data collected during this study, suggested that the northwest Minnesota moose population likely would not persist over the next 50 years. More broadly, we conclude that the southern distribution of moose may become restricted in areas where climate and habitat conditions are marginal, especially where deer are abundant and act as reservoir hosts for parasites.

Minnesota↗

USGS2008

Elk calf survival and mortality following wolf restoration to Yellowstone National Park

We conducted a 3‐year study (May 2003–Apr 2006) of mortality of northern Yellowstone elk ( Cervus elaphus ) calves to determine the cause for the recruitment decline (i.e., 33 calves to 13 calves/100 adult F) following the restoration of wolves ( Canis lupus ). We captured, fit with radiotransmitters, and evaluated blood characteristics and disease antibody seroprevalence in 151 calves ≤6 days old (68M:83F). Concentrations (x̄, SE) of potential condition indicators were as follows: thyroxine (T4; 13.8 μg/dL, 0.43), serum urea nitrogen (SUN; 17.4 mg/dL, 0.57), γ‐glutamyltransferase (GGT; 66.4 IU/L, 4.36), gamma globulins (GG; 1.5 g/dL, 0.07), and insulin‐like growth factor‐1 (IGF‐1; 253.6 ng/mL, 9.59). Seroprevalences were as follows: brucellosis ( Brucella abortus ; 3%), bovine‐respiratory syncytial virus (3%), bovine‐viral‐diarrhea virus type 1 (25%), infectious‐bovine rhinotracheitis (58%), and bovine parainfluenza‐3 (32%). Serum urea nitrogen, GGT, GG, and IGF‐1 varied with year; T4, SUN, and GG varied with age ( P ≤ 0.01); and SUN varied by capture area ( P = 0.02). Annual survival was 0.22 (SE = 0.035, n = 149) and varied by calving area but not year. Neonates captured in the Stephens Creek/Mammoth area of Yellowstone National Park, USA, had annual survival rates >3× higher (0.54) than those captured in the Lamar Valley area (0.17), likely due to the higher predator density in Lamar Valley. Summer survival (20 weeks after radiotagging) was 0.29 (SE = 0.05, n = 116), and calving area, absolute deviation from median birth date, and GG were important predictors of summer survival. Survival during winter (Nov‐Apr) was 0.90 (SE= 0.05, n = 42), and it did not vary by calving area or year. Sixty‐nine percent ( n = 104) of calves died within the first year of life, 24% ( n = 36) survived their first year, and 7% ( n = 11) had unknown fates. Grizzly bears ( Ursus arctos ) and black bears ( Ursus americanus ) accounted for 58–60% ( n = 60–62) of deaths, and wolves accounted for 14–17% ( n = 15–18). Summer predation (95% of summer deaths) increased, and winter malnutrition (0% of winter deaths) decreased, compared with a similar study during 1987–1990 (72% and 58%, respectively). Physiological factors (e.g., low levels of GG) may predispose calves to predation. Also, the increase in bear numbers since wolf restoration and spatial components finer than the northern range should be considered when trying to determine the causes of the northern Yellowstone elk decline. This is the first study to document the predation impacts from reintroduced wolves on elk calf mortality in an ecosystem already containing established populations of 4 other major predators (i.e., grizzly and black bears, cougars [ Puma concolor ], and coyotes [ Canis latrans ]). The results are relevant to resource managers of the Yellowstone ecosystem in understanding the dynamics of the elk population, in providing harvest quota recommendations for local elk hunts to the Montana Department of Fish, Wildlife and Parks, the United States Fish and Wildlife Service regarding wolf and grizzly bear recovery, and to all areas worldwide where predators are increasing, by providing managers with information about potential carnivore impacts on elk populations.

Idaho, Montana, Wyoming↗