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At least 253 records · Page 14Linked to original sources
USGS1998

Using transport model interpretations of tracer tests to study microbial processes in groundwater

It has long been known that microorganisms affect the geochemistry of groundwater. But despite this recognition, little detailed information is available regarding the rates and the factors controlling microbial processes in groundwater. Part of the reason stems from the relatively inaccessible nature of most groundwater and the difficulties encountered in obtaining representative samples of groundwater and subsurface sediments. At the same time, most groundwater systems are nutrient poor or oligotrophic environments in which the resident microorganisms are severely stressed and often nearly inactive. These populations are functioning so slowly that many types of activity measurements designed to assess microbial processes in more productive environments are ineffective for groundwater. However, because groundwater is by far the largest reservoir of freshwater in the world ( Freeze and Cherry 1979 ), our lack of knowledge about groundwater microorganisms and their processes represents a significant void in the study of microbial ecology and in our ability to predict the outcome when these reserves are compromised by contamination.

Book chapter↗
USGS2025

Mountain sentinels in a changing world: Review and conservation implications of weather and climate effects on mountain goats (Oreamnos americanus)

Climate change is occurring at an accelerated rate in high-elevation alpine and mountain ecosystems. Cold-adapted, mountain species are at risk due to forecasted change and knowledge is needed to respond to current and future conservation challenges. Mountain goats ( Oreamnos americanus ) are an iconic species of North American mountain cultures and landscapes, and due to specialized adaptations for life in cold, mountainous environments they are particularly sensitive to changes in weather and climate. As sentinels of change in alpine ecosystems, the study of mountain goats offers insight into the ecological effects and conservation challenges associated with climate change in these sensitive and biodiverse environments. Here, we synthesize existing knowledge about how climate change is expected to influence environmental conditions experienced by mountain goats and associated mechanistic changes to behavior, nutritional ecology, demography, health, and interspecific interactions. In many instances, climate change effects are likely to be negative and additive to existing threats (such as human disturbance, hunting, disease, predation) though benefits are expected in some cases. Changes in climate and mountain environments will necessitate re-examination and modification of population monitoring, management, and conservation strategies. Specifically, spatiotemporal (and other) aspects of monitoring and management may need to be adjusted to accommodate emerging and novel conservation challenges. Yet, key data and knowledge gaps remain and should be addressed to advance conservation and decision-making capabilities. For mountain goats and similarly climate-sensitive alpine herbivores, effective conservation will ultimately benefit from collaborations among diverse networks guided by well-planned, strategic visions focused on common ground – namely the resiliency and persistence of culturally and ecologically significant mountain species and the alpine environment they inhabit.

Alaska, Alberta, British Columbia, Idaho, Montana,↗
USGS2019

Nonlinear reaction–diffusion process models improve inference for population dynamics

Partial differential equations (PDEs) are a useful tool for modeling spatiotemporal dynamics of ecological processes. However, as an ecological process evolves, we need statistical models that can adapt to changing dynamics as new data are collected. We developed a model that combines an ecological diffusion equation and logistic growth to characterize colonization processes of a population that establishes long-term equilibrium over a heterogeneous environment. We also developed a homogenization strategy to statistically upscale the PDE for faster computation and adopted a hierarchical framework to accommodate multiple data sources collected at different spatial scales. We highlighted the advantages of using a logistic reaction component instead of a Malthusian component when population growth demonstrates asymptotic behavior. As a case study, we demonstrated that our model improves spatiotemporal abundance forecasts of sea otters in Glacier Bay, Alaska. Furthermore, we predicted spatially varying local equilibrium abundances as a result of environmentally driven diffusion and density-regulated growth. Integrating equilibrium abundances over the study area in our application enabled us to infer the overall carrying capacity of sea otters in Glacier Bay, Alaska.

Alaska↗
USGS2011

Biology, status, and management of the yellowstone cutthroat trout

Yellowstone cutthroat trout Oncorhynchus clarkii bouvieri were historically distributed in the Yellowstone River drainage (Montana and Wyoming) and the Snake River drainage (Wyoming, Idaho, Utah, Nevada, and probably Washington). Individual populations evolved distinct life history characteristics in response to the diverse environments in which they were isolated after the last glaciation. Anthropogenic activities have resulted in a substantial decline (42% of the historical range is currently occupied; 28% is occupied by core [genetically unaltered] populations), but the number of extant populations, especially in headwater streams, has precluded listing of this taxon under the Endangered Species Act. Primary threats to persistence of Yellowstone cutthroat trout include (1) invasive species, resulting in hybridization, predation, disease, and interspecific competition; (2) habitat degradation from human activities such as agricultural practices, water diversions, grazing, dam construction, mineral extraction, grazing, timber harvest, and road construction; and (3) climate change, including an escalating risk of drought, wildfire, winter flooding, and rising temperatures. Extirpation of individual populations or assemblages has led to increasing isolation and fragmentation of remaining groups, which in turn raises susceptibility to the demographic influences of disturbance (both human and stochastic) and genetic factors. Primary conservation strategies include (1) preventing risks associated with invasive species by isolating populations of Yellowstone cutthroat trout and (2) connecting occupied habitats (where possible) to preserve metapopulation function and the expression of multiple life histories. Because persistence of isolated populations may be greater in the short term, current management is focused on isolating individual populations and restoring habitats; however, this approach implies that humans will act as dispersal agents if a population is extirpated because of stochastic events.

Idaho, Montana, Utah, Wyoming↗
USGS2019

Pleistocene glacial cycles drove lineage diversification and fusion in the Yosemite toad (Anaxyrus canorus)

Species endemic to alpine environments can evolve via steep ecological selection gradients between lowland and upland environments. Additionally, many alpine environments have faced repeated glacial episodes over the past two million years, fracturing these endemics into isolated populations. In this “glacial pulse” model of alpine diversification, cycles of allopatry and ecologically divergent glacial refugia play a role in generating biodiversity, including novel admixed (“fused”) lineages. We tested for patterns of glacial pulse lineage diversification in the Yosemite toad ( Anaxyrus [ Bufo ] canorus ), an alpine endemic tied to glacially influenced meadow environments. Using double‐digest RADseq on populations densely sampled from a portion of the species range, we identified nine distinct lineages with divergence times ranging from 18 to 724 thousand years ago (ka), coinciding with multiple Sierra Nevada glacial events. Three lineages have admixed origins, and demographic models suggest these fused lineages have persisted throughout past glacial cycles. Directionality indices supported the hypothesis that some lineages recolonized Yosemite from east of the ice sheet, whereas other lineages remained in western refugia. Finally, refugial niche reconstructions suggest that low‐ and high‐elevation lineages have convergently adapted to similar climatic niches. Our results suggest glacial cycles and refugia may be important crucibles of adaptive diversity across deep evolutionary time.

California↗
USGS2005

Interaction of beaver and elk herbivory reduces standing crop of willow

Populations of beaver and willow have not thrived in riparian environments that are heavily browsed by livestock or ungulates, such as elk. The interaction of beaver and elk herbivory may be an important mechanism underlying beaver and willow declines in this competitive environment. We conducted a field experiment that compared the standing crop of willow three years after simulated beaver cutting on paired plants with and without intense elk browsing (∼85% utilization rate). Simulated beaver cutting with intense elk browsing produced willow that was small (biomass and diameter) and short, with far fewer, but longer, shoots and a higher percentage of dead biomass. In contrast, simulated beaver cutting without elk browsing produced willow that was large, tall, and leafy, with many more, but shorter, shoots (highly branched) and a lower percentage of dead biomass. Total stem biomass after three years was 10 times greater on unbrowsed plants than on browsed plants. Unbrowsed plants recovered 84% of their pre-cut biomass after only two growing seasons, whereas browsed plants recovered only 6%. Thus, the interaction of beaver cutting and elk browsing strongly suppressed the standing crop of willow. We predict that a lack of willow suitable as winter food for beaver can cause beaver populations to decline, creating a feedback mechanism that reduces beaver and willow populations. Thus, intense herbivory by ungulates or livestock can disrupt beaver–willow mutualisms that naturally occur in less competitive environments.

Ecological Applications↗
USGS2007

Variability of kokanee and rainbow trout food habits, distribution, and population dynamics, in an ultraoligotrophic lake with no manipulative management

Crater Lake is a unique environment to evaluate the ecology of introduced kokanee and rainbow trout because of its otherwise pristine state, low productivity, absence of manipulative management, and lack of lotic systems for fish spawning. Between 1986 and 2004, kokanee displayed a great deal of variation in population demographics with a pattern that reoccurred in about 10 years. We believe that the reoccurring pattern resulted from density dependent growth, and associated changes in reproduction and abundance, driven by prey resource limitation that resulted from low lake productivity exacerbated by prey consumption when kokanee were abundant. Kokanee fed primarily on small-bodied prey from the mid-water column; whereas rainbow trout fed on large-bodied prey from the benthos and lake surface. Cladoceran zooplankton abundance may be regulated by kokanee. And kokanee growth and reproductive success may be influenced by the availability of Daphnia pulicaria, which was absent in zooplankton samples collected annually from 1990 to 1995, and after 1999. Distribution and diel migration of kokanee varied over the duration of the study and appeared to be most closely associated with prey availability, maximization of bioenergetic efficiency, and fish density. Rainbow trout were less abundant than were kokanee and exhibited less variation in population demographics, distribution, and food habits. There is some evidence that the population dynamics of rainbow trout were in-part related to the availability of kokanee as prey. ?? 2007 Springer Science+Business Media B.V.

Hydrobiologia↗
USGS2018

Application of the Stream Salmonid Simulator (S3) to the restoration reach of the Trinity River, California—Parameterization and calibration

Executive Summary In this report, we constructed and parameterized the Stream Salmonid Simulator (S3) for the 64-kilometer “Restoration Reach” of the Trinity River, just downstream of Lewiston Dam in northern California. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive survival and growth within each habitat unit and movement of fish among habitat units. The physical template of the Restoration Reach was formed by classifying the river into 356 meso-habitat units comprised of runs, riffles, and pools. For each habitat unit, we developed a timeseries of daily flow, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg growth and survival and juvenile movement, growth, and survival.

California↗
USGS2025

Calibration of the Stream Salmonid Simulator (S3) model to estimate annual survival, movement, and food consumption by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the restoration reach of the Trinity River, California, 2006–18

Executive Summary The Trinity River is managed in two sections: (1) from the upper 64-kilometer “restoration reach” downstream from Lewiston Dam to the confluence with the North Fork Trinity River, and (2) the 120-kilometer lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously applied to these reaches and the Klamath River. To estimate fish growth, past S3 calibration efforts in the Trinity and Klamath Rivers used maximum likelihood methods that considered only the abundance of juvenile Chinook salmon ( Oncorhynchus tshawytscha ) passing a fish trap to estimate survival and movement parameters, but not fish consumption. Previous calibrations did not estimate the average proportion of maximum consumption ( C y ) when estimating survival ( S y ) and movement ( M 0 y ) parameters across years ( y ) of data, but because no other information was available in the literature a fixed value of C y =0.66 was assumed. Therefore, the goal of this report is to present an alternative approach that calibrates the S3 model to multivariate data (that is, abundance and size), enabling the estimation of the average proportion of maximum consumption, in conjunction with survival and movement parameters for a particular migration year. We fit the S3 model to individual years of weekly trap abundance estimates and mean fish sizes (fork length) at the Pear Tree Gulch (hereafter referred to as Pear Tree) fish trap representing the restoration reach. We used the Earth Mover’s Distance (EMD) as the objective value to be minimized in parameter optimization. This approach estimated survival, movement, and consumption parameters for each migration year. Because we had information on the abundance of natural and hatchery produced juvenile salmon at the fish traps, we estimated survival and movement for natural and hatchery fish. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile Chinook Salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive survival and growth within each habitat unit and movement of fish among habitat units. The physical template of the restoration reach of the Trinity River was classified into 356 meso-habitat units comprised of runs, riffles, and pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity time series were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival. We estimated movement, survival, and consumption parameters by calibrating the model to 12 years of weekly juvenile abundance estimates and fish sizes at the Pear Tree fish trap near the downstream end of the restoration reach. We estimated parameters for 12 years that included a wide range of female spawner abundances (1,414–11,494) and water year types (critically dry–extremely wet). We contrast the estimated parameters to the corresponding number of female spawners and the total annual volume of water discharged for the Trinity River (Trinity River Restoration Program; https://www.trrp.net/restoration/flows/summary/ ). The calibration consisted of replicating historical conditions as closely as possible (for example, discharge; temperature; spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location from each brood year of adults and subsequent migration year of their juvenile progeny. Because density-dependent movement was favored in past evaluations, we estimated S3 parameters based on density-independent survival and density-dependent movement. Likewise, each year’s estimated survival parameter for natural ( S N y ) and hatchery ( S H y ) fish may be interpreted as the mean daily survival probability from emergence or hatchery release to the Pear Tree fish trap. Under density dependence, the estimated movement parameter for natural ( M 0N y ) and hatchery ( M 0H y ) fish represents the intercept of the Beverton-Holt model; the probability of remaining in a habitat at near-zero abundance. We estimated C y by using EMD and incorporating abundance and fish size into model calibration. Average daily proportions of maximum consumption, , across the years were generally high (=0.640; standard deviation (SD) SD=0.176), suggesting that fish were feeding at about two-thirds of expected maximum consumption rates. This average proportion of maximum consumption,is very similar to what has been assumed (=0.66) in previous Trinity and Klamath River S3 calibration and simulation efforts. In 2017, we estimated the lowest C y , suggesting lower average consumption for juvenile salmon in high-discharge water years. When this high discharge year was excluded, there was no apparent trend in C y with annual water volume. Estimates of survival showed little trend over the range in spawner abundances, but a trend towards higher natural and hatchery fish survival with higher annual volumes of water was apparent. Over the 12 years, the average survival of hatchery fish was =0.888 (SD=0.079) and the average survival natural fish was=0.969 (SD=0.01). With respect to fish movement, we estimated higher M 0N y and M 0H y with higher annual volumes of water in the Trinity River. Higher M N0 y or M H0 y suggest greater probability of remaining in a habitat at low fish densities, with potential for density-dependent processes in movement to occur. The highest M 0N y = 0.676 was estimated during brood year 2012, and the overall average for natural fish was =0.276 (SD=0.188) and for hatchery fish was=0.467 (SD=0.235). Under the Beverton-Holt model, as M 0N y or M 0H y approach zero, there is less capacity for change in fish movement as fish density increases. The S3 model was initialized with only the spatiotemporal distribution of spawners, so it performed well at capturing the essential outmigration features that are ultimately governed by rates of growth, movement, and mortality. We used a new optimization method that could accommodate multivariate data on abundance and fish size collected at the Pear Tree fish trap, enabling the calibration of S3 to estimate five parameters for 12 separate years of data. Incorporating weekly fish size data for each year in our parameter optimization process made the estimation of C y possible and represents a step forward in the fitting of the S3 model to fish trap data for the purposes of parameter calibration and the estimation of growth parameters with respect to annual conditions. We identified lack of fit and adding important effects into the S3 model may improve the S3 estimation and simulation of water scenarios. The Trinity River Restoration Program (TRRP) Science Advisory Board recommended that the TRRP focus on developing core elements of a decision support system (DSS; Buffington and others, 2014). Toward that end, the habitat and S3 models described in this report are both core elements of the DSS. The structure of S3 makes it a particularly useful fish production model for the DSS because population dynamics are sensitive to (1) water temperature, (2) daily discharge management, and (3) habitat quality and quantity. Each of these variables are key management parameters under consideration in the TRRP. As such, the S3 model may provide valuable insights into the potentially variable effects of different management decisions on the Trinity River.

California↗
USGS2023

Calibration of the Trinity River Stream Salmonid Simulator (S3) with extension to the Klamath River, California, 2006–17

The Trinity River is managed in two sections: (1) the upper 64-kilometer (km) “restoration reach” downstream from Lewiston Dam and (2) the 120-km lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously constructed and calibrated for the restoration reach. In this report, we extended and parameterized S3 for the 120-km section of the lower Trinity River to the confluence with the Klamath River and then to the Pacific Ocean in northern California. S3 is a deterministic life-stage structured-population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive (1) survival and growth within each habitat unit and (2) movement of fish among habitat units. The physical template of the Trinity River was formed by classifying the river into 910 meso-habitat units that were designated into runs, riffles, or pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival. We estimated key movement and survival parameters by calibrating the model to 12 years (2007–18) of weekly juvenile abundance estimates from two rotary screw traps: (1) the Pear Tree trap near the downstream end of the restoration reach and (2) the Willow Creek trap site is about 40.2 km upriver from the Trinity River’s confluence with the Klamath River. The calibration consisted of replicating historical conditions as closely as possible (for example: flow, temperature, spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location. We also evaluated four alternative model structures that included either no density-dependence, density-independent movement and survival, density-dependent survival, or density-dependent movement. Akaike information criterion model selection was used to evaluate the strength of evidence for alternative model structures to simulate the observed abundance estimates. Model selection supported the conclusion that the fully density-dependent model and density-dependent survival model was better supported by the data than the no density-dependence or density-dependent movement model. Because density-dependent movement was favored in past evaluations, we focus on the results from the fully density-dependent model. Parameter estimates from this model indicated that fry were less likely than parr to move downstream and that fry moved slower. Fry had a lower daily survival probability than parr. In contrast, hatchery fish had the highest probability of movement and the lowest daily survival probability. Fitting the model to both traps individually enabled us to independently compare the fit and performance of S3 at simulating fish abundance, timing, and growth of juvenile salmon in the upper restoration reach and lower Trinity River. We obtained a better fit to the data at the Willow Creek trap site than we obtained at the Pear Tree trap site, regardless of whether we fit the model to the abundances at the Pear Tree trap or Willow Creek trap. This better fit was surprising given that the S3 input data for the upper restoration reach required fewer assumptions than fitting to the Willow Creek trap site that is farther down river. Fitting S3 to weekly abundances at the Willow Creek trap site required making assumptions about (1) extrapolating capacity-flow relationships to unmeasured habitat units; (2) spatially allocating spawners within the lower Trinity River; and (3) approximating the abundance, timing, and size of juveniles entering from tributaries. The model provided better fit to the data at the Willow Creek trap site. In the weekly abundance estimates, in relation to the S3 simulated abundances, several migration years’ (2011, 2015–17) weekly abundance estimates appeared truncated and were near or at peak annual abundances in January, suggesting that a large fraction of juveniles was migrating as early as December at the Pear Tree trap site. Some early life dynamics may not be currently incorporated into S3. For example, the estimation of abundance at the Pear Tree trap may be biased because of size selectivity. Knowing about selectivity at the Pear Tree trap could greatly improve S3’s ability to predict weekly and peak abundances each year.

California↗
USGS2018

Model structure of the stream salmonid simulator (S3)—A dynamic model for simulating growth, movement, and survival of juvenile salmonids

Fisheries and water managers often use population models to aid in understanding the effect of alternative water management or restoration actions on anadromous fish populations. We developed the Stream Salmonid Simulator (S3) to help resource managers evaluate the effect of management alternatives on juvenile salmonid populations. S3 is a deterministic stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and usable habitat area or carrying capacity. The physical characteristics of each habitat unit and the number of fish occupying each unit, in turn, drive survival and growth within each habitat unit and movement of fish among habitat units. The purpose of this report is to outline the underlying general structure of the S3 model that is common among different applications of the model. We have developed applications of the S3 model for juvenile fall Chinook salmon ( Oncorhynchus tshawytscha ) in the lower Klamath River. Thus, this report is a companion to current application of the S3 model to the Trinity River (in review). The general S3 model structure provides a biological and physical framework for the salmonid freshwater life cycle. This framework captures important demographics of juvenile salmonids aimed at translating management alternatives into simulated population responses. Although the S3 model is built on this common framework, the model has been constructed to allow much flexibility in application of the model to specific river systems. The ability for practitioners to include system-specific information for the physical stream structure, survival, growth, and movement processes ensures that simulations provide results that are relevant to the questions asked about the population under study.

Open-File Report↗
USGS2019

Temporally adaptive acoustic sampling to maximize detection across a suite of focal wildlife species

Acoustic recordings of the environment can produce species presence–absence data for characterizing populations of sound-producing wildlife over multiple spatial scales. If a species is present at a site but does not vocalize during a scheduled audio recording survey, researchers may incorrectly conclude that the species is absent (“false negative”). The risk of false negatives is compounded when audio devices have sampling constraints, do not record continuously, and must be manually scheduled to operate at pre-selected times of day, particularly when research programs target multiple species with acoustic availability that varies across temporal conditions. We developed a temporally adaptive acoustic sampling algorithm to maximize detection probabilities for a suite of focal species amid sampling constraints. The algorithm combines user-supplied species vocalization models with site-specific weather forecasts to set an optimized sampling schedule for the following day. To test our algorithm, we simulated hourly vocalization probabilities for a suite of focal species in a hypothetical monitoring area for the year 2016. We conducted a factorial experiment that sampled from the 2016 acoustic environment to compare the probability of acoustic detection by a fixed (stationary) schedule versus a temporally adaptive optimized schedule under several sampling efforts and monitoring durations. We found that over the course of a study season, the probability of acoustically capturing a focal species (given presence) at least once via automated acoustic monitoring was greater (and acoustic capture occurred earlier in the season) when using the temporally adaptive optimized schedule as compared to a fixed schedule. The advantages of a temporally adaptive optimized acoustic sampling schedule are magnified when a study duration is short, sampling effort is low, and/or species acoustic availability is minimal. This methodology presents the opportunity to maximize acoustic monitoring sampling efforts amid constraints.

Colorado↗
USGS2020

“Good” and “bad”: Human perceptions of and interactions with urban wildlife

Urban environments offer habitat for many species of animals. Although some of those are ubiquitous and/or undesirable, others are native and in some cases, of conservation value. In many cases, urban wildlife populations are a source of enjoyment for human residents, who sometimes invest considerable amounts in attracting them to yards and public spaces. Their presence there can serve an important educational role that helps protect non-urban habitats and species. Nonetheless, urban wildlife must survive what has been termed a “landscape of fear.” Although some of the urban wildlife that do well in this environment are benign, other populations – sometimes of a species that, in other locations, is iconic and desirable – can become problematic. Some species can serve as vectors that carry important zoonosis, such as the plague or diseases that affect other wildlife. Others can create noise or olfactory nuisances and degrade structures or usability of public spaces. Some pose hazards at busy airports, whereas still others may present an envenomation or predation risk on unwary humans. Here, we review the role that reptiles, birds, and mammals play in urban environments and discuss how urban wildlife rehabilitation centers help address some related issues. We close by looking ahead and trying to predict how global patterns such as increased urbanization and population growth may affect urban wildlife and its value for conservation.

Book chapter↗
USGS1985

Toxic materials, fishing, and environmental variation: Simulated effects on striped bass population trends

Decreased survival of larval striped bass Morone saxatilis resulting from toxic chemicals in the environment and decreased survival of adults caused by fishing both are suspected as agents contributing to the decline in the Chesapeake Bay stock since the mid‐1970s. The relative power of each type of mortality to cause population declines was evaluated with simulation techniques. Equivalent levels of added mortality induced qualitatively identical and quantitatively similar trends in population simulations for all conditions examined except if strong density‐dependent mortality preceded the contaminant toxicity. In this case the contaminant effect caused a greater reduction in yield, but the population did not tend toward extinction. The results indicate that the observed downward trend in the Chesapeake Bay population can be halted or reversed by a reduction in fishing mortality, even if contaminant toxicity is the proximate cause for the decline.

Maryland↗
USGS2019

Application of the Stream Salmonid Simulator (S3) to Klamath River fall Chinook salmon (Oncorhynchus tshawytscha), California—Parameterization and calibration

Executive Summary In this report, we describe application of the Stream Salmonid Simulator (S3) to Chinook salmon ( Oncorhynchus tshawytscha ) in the Klamath River between Keno Dam in southern Oregon and the ocean in northern California. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. It can track different source populations or species, such as major tributary populations that enter a river like the Klamath River. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit affect survival and growth within each habitat unit and movement of fish among habitat units. The physical template of the Klamath River was formed by classifying the river into 2,635 mesohabitat units composed of runs, riffles, and pools. This template enabled modeling of the unimpounded Klamath River between the Keno Dam (the uppermost of four dams) and Iron Gate Dam (the lowermost dam) to address dam-removal scenarios. However, in this report, our focus was on parameterizing and calibrating the model under existing conditions, which included 1,706 discrete habitat units over the 312-kilometer (km) section of river between Iron Gate Dam and the ocean. For each habitat unit, we developed a time series of daily flow, water temperature, and amount of available habitat (weighted usable habitat area [WUA]) for spawners, fry, and parr. WUA time series were constructed using habitat suitability criteria for Chinook salmon applied to eight two-dimensional (2-D) hydrodynamic models that represented the geomorphic variability in habitat across the Klamath River. Results from the 2-D models were then extrapolated to unmodeled habitat units by scaling WUA curves for changes in habitat unit length and width. These variables were then used to drive population dynamics such as egg development and survival and juvenile movement, growth, and survival.

California, Oregon↗
USGS2015

Gene transcription in polar bears ( Ursus maritimus ) from disparate populations

Polar bears in the Beaufort (SB) and Chukchi (CS) Seas experience different environments due primarily to a longer history of sea ice loss in the Beaufort Sea. Ecological differences have been identified as a possible reason for the generally poorer body condition and reproduction of Beaufort polar bears compared to those from the Chukchi, but the influence of exposure to other stressors remains unknown. We use molecular technology, quantitative PCR, to identify gene transcription differences among polar bears from the Beaufort and Chukchi Seas as well as captive healthy polar bears. We identified significant transcriptional differences among a priori groups (i.e., captive bears, SB 2012, SB 2013, CS 2013) for ten of the 14 genes of interest (i.e., CaM, HSP70, CCR3, TGFβ, COX2, THRα, T-bet, Gata3, CD69, and IL17); transcription levels of DRβ, IL1β, AHR, and Mx1 did not differ among groups. Multivariate analysis also demonstrated separation among the groups of polar bears. Specifically, we detected transcript profiles consistent with immune function impairment in polar bears from the Beaufort Sea, when compared with Chukchi and captive polar bears. Although there is no strong indication of differential exposure to contaminants or pathogens between CS and SB bears, there are clearly differences in important transcriptional responses between populations. Further investigation is warranted to refine interpretation of potential effects of described stress-related conditions for the SB population.

Polar Biology↗
USGS2021

The role of genome duplication in big sagebrush growth and fecundity

Premise Adaptive traits can be dramatically altered by genome duplication. The study of interactions among traits, ploidy, and the environment are necessary to develop an understanding of how polyploidy affects niche differentiation and to develop restoration strategies for resilient native ecosystems. Methods Growth and fecundity were measured in common gardens for 39 populations of big sagebrush ( Artemisia tridentata ) containing two subspecies and two ploidy levels. General linear mixed-effect models assessed how much of the trait variation could be attributed to genetics (i.e., ploidy and climatic adaptation), environment, and gene–environment interactions. Results Growth and fecundity variation were explained well by the mixed models (80% and 91%, respectively). Much of the trait variation was attributed to environment, and 15% of variation in growth and 34% of variation in seed yield were attributed to genetics. Genetic trait variation was mostly attributable to ploidy, with much higher growth and seed production in diploids, even in a warm-dry environment typically dominated by tetraploids. Population-level genetic variation was also evident and was related to the climate of each population's origin. Conclusions Ploidy is a strong predictor growth and seed yield, regardless of common-garden environment. The superior growth and fecundity of diploids across environments raises the question as to how tetraploids can be more prevalent than diploids, especially in warm-dry environments. Two hypotheses that may explain the abundance of tetraploids on the landscape include selection for drought resistance at the seedling stage, and greater competitive ability in water uptake in the upper soil horizon.

American Journal of Botany↗
USGS2022

Variation of cisco egg size among Laurentian Great Lakes populations

Many fish species display inter-population and inter-individual egg size variation. Intra-specific differences in egg size seemingly reflect both energetic experiences of individual spawning fish and long-term population responses to differing ecosystems. Optimal egg size theory implies that selection influences a population’s mean egg size in response to its early-life environment, given the well-established trade-off between egg size and fecundity. Currently, there is strong interest in rehabilitation of Laurentian Great Lakes cisco, Coregonus artedi, which is characterized by inter-population variation of morphological and behavioral traits. However, the extent of cisco egg size variation is under-described. In fall 2018 and 2019, we collected egg samples by stripping ripe females at seven total locations in four Great Lakes. We measured unfertilized egg diameters using imaging software and compared mean egg diameters among locations with and without including maternal total length as a covariate. Lake Michigan females produced the largest eggs overall but were excluded from analyses using the total length covariate because of their significantly larger body sizes. Maternal length had a positive effect on egg size, and when accounting for this effect, females in Lake Huron produced the largest eggs followed by Lake Ontario and Lake Superior. We also found that egg size varied among locations within Lake Superior. These findings aligned with observations of morphological and behavioral differences among populations and suggest that cisco phenotypic variation at a fine spatial scale extends to reproductive biology. Consideration of cisco reproductive traits, such as egg size, may inform restoration strategies, including supplemental stocking.

Journal of Great Lakes Research↗