Geology topics

James T. Peterson

Publications and source records attributed to James T. Peterson.

At least 55 records · Page 3Linked to original sources

USGS2020

Concealment of juvenile bull trout in response to temperature, light, and substrate: Implications for detection

Bull trout ( Salvelinus confluentus) are challenging to detect as a result of the species cryptic behavior and coloration, relatively low densities in complex habitats, and affinity for cold, high clarity, low conductivity waters. Bull trout are also closely associated with the stream bed, frequently conceal in substrate, and this concealment behavior is poorly understood. Consequently, population assessments are problematic and biologists and managers often lack quantitative information to accurately describe bull trout distributions, estimate abundance, and assess status and trends; particularly for stream-dwelling populations. During controlled laboratory trials, we recorded concealment, resting, and swimming behavior of juvenile wild bull trout in response to: (1) constant and fluctuating water temperature, (2) presence or absence of light, and (3) substrate size. Light level had the strongest influence on wild fish concealment and more fish concealed as light levels increased from darkness to daylight. Wild fish were 14.5 times less likely to conceal in constant darkness and 4.1 times more likely to conceal in 12 h light x 12 h darkness compared to constant light. Wild fish were 6.2 times less likely to conceal in small (26–51 mm) substrate compared to larger (52–102 mm) substrate. As water temperature increased, fewer wild fish concealed. Knowledge of wild bull trout concealment will improve field sampling protocols and increase detection efficiencies. These data also enhance knowledge of bull trout niche requirements which illuminates ecological differences among species and informs conservation and restoration efforts.

PLoS ONE↗

USGS2020

Using a bayesian multistate occupancy model to assess seabird and shorebird status in Glacier Bay, Alaska

The U.S. Department of Interior National Park Service is charged with both monitoring avian communities and evaluating the influence of visitors to National Parks on sensitive species; however, this task is challenging considering that sampling programs often involve multiple species, each with differing behavior, habitat requirements, and detectability. Our objectives were to build a model to describe the status of waterbirds in Glacier Bay National Park, Alaska, USA, and assess effects of area closures on these species. We used a Bayesian multistate occupancy model to describe the status of multiple species and make the best possible use of existing survey data. We modeled up to 5 states per species and evaluated predictors of occupancy, nesting, and abundance, as well as survey-related predictors of state-dependent detection probability. We found that occupancy probability varied across species and habitats (islands vs. glacial outwashes). For most species, occupancy probability was substantially greater at sites occupied in the year previous (site persistence). We found weak evidence that area closures affected the occurrence of species in the study, but this was largely because most sites were closed for the entirety of the study period. The probability of detecting occurrence, nesting, and abundance varied across species and survey methods (ground vs. vessel). Detection parameters provided valuable information for enhancing the efficiency of future surveys, by identifying preferred survey methods and sampling periods for specific waterbird species. © 2020 The Wildlife Society.

Alaska↗

USGS2020

Estimation of metademographic rates and landscape connectivity for a conservation-reliant anuran

Context Amphibian conservation efforts commonly assume populations are tied to waterbodies that collectively function as a metapopulation. This assumption is rarely evaluated, and there is a need to understand the degree of connectivity among patches to appropriately define, manage, and conserve biological populations. Objectives Our objectives were to quantify local persistence, colonization, and recruitment (metademographic rates) in relation to habitat attributes, evaluate the influence of the spatial arrangement of patches on landscape-scale population dynamics, and estimate the scale at which metapopulation dynamics are occurring for Oregon spotted frog ( Rana pretiosa ). Methods We collected R. pretiosa detection/non-detection data and habitat information from 93 sites spread throughout the species’ extant range in Oregon, USA, 2010–2018. We developed a spatial multistate dynamic occupancy model to analyze these data. Results The proportion of sites occupied by R. pretiosa was relatively stable despite regular turnover in site occupancy. Connectivity was greatest when the distance between sites was within 4.49–7.70 km, and the results suggested that populations within 1 km are at the appropriate spatial scale for effective population management. Rana pretiosa metademographic rates were strongly tied to water availability, vegetation characteristics, and beaver dams. Conclusions Our analysis provides critical information to identify the appropriate spatial scale for effective population management, estimates the distance at which populations are connected, and quantifies the effects of hypothesized threats to species at a landscape scale. We believe this model will prove to be useful to inform conservation and management strategies for multiple species.

Oregon↗

USGS2020

Comparing environmental flow implementation options with structured decision making: Case study from the Willamette River, Oregon

Many frameworks have been used to identify environmental flows for sustaining river ecosystems or specific taxa in the face of widespread flow alteration for human use. However, these methods mostly focus on identifying suitable flows and largely ignore the important links between management actions, resulting flows, flow variability, and ecosystem or social responses. Structured decision making (SDM) could assist the comparison and implementation of environmental flows by providing a framework to compare effects of flow management actions on objectives via environmental flow science. We describe the SDM process and illustrate its application using a case study focused on comparing environmental flow scenarios for the mainstem Willamette River, Oregon, USA. In a short timeframe, SDM was successfully applied to identify management objectives, develop empirical and expert opinion based models predicting ecological responses, and compare scenarios while accounting for uncertainty and partial controllability. We found that no flow scenario was clearly preferred based on available knowledge, largely because river flows could only be partially controlled through available dam operations. Participants agreed that the SDM process was useful and that an additional iteration focused on refining predictive models and incorporating additional objectives could help better inform dam release decisions for the entire basin. In our view, SDM can provide managers with more realistic comparisons of environmental flows by accounting for partial controllability and uncertainty, which may result in greater implementation of available flow management actions.

Oregon↗

USGS2020

Modelling pinniped abundance and distribution by combining counts at terrestrial sites and in-water sightings

Pinnipeds are commonly monitored using aerial photographic surveys at land- or ice-based sites, where animals come ashore for resting, pupping, molting, and to avoid predators. Although these counts form the basis for monitoring population change over time, they do not provide information regarding where animals occur in the water, which is often of management and conservation interest. In this study, we developed a hierarchical model that links counts of pinnipeds at terrestrial sites to sightings-at-sea and estimates abundance, spatial distribution, and the proportion of time spent on land (attendance probability). The structure of the model also allows for the inclusion of predictors that may explain variation in ecological and observation processes. We applied the model to Steller sea lions ( Eumetopias jubatus ) in Glacier Bay, Alaska using counts of sea lions from aerial photographic surveys and opportunistic in-water sightings from vessel surveys. Glacier Bay provided an ideal test and application of the model because data are available on attendance probability based on long-term monitoring. We found that occurrence in the water was positively related to proximity to terrestrial sites, as would be expected for a species that engages in central-place foraging. The proportion of sea lions in attendance at terrestrial sites and overall abundance estimates were consistent with reports from the literature and monitoring programs. The model we describe has benefit and utility for park managers who wish to better understand the overlap between pinnipeds and visitors, and the framework that we present has potential for application across a variety of study systems and taxa.

Alaska↗

USGS2020

Odds ratios and hurdle models: a long-term analysis of parasite infection patterns in endangered young-of-the-year suckers from Upper Klamath Lake, Oregon, USA

We used odds ratios and a hurdle model to analyze parasite co-infections over 25 years on >20,000 young-of-the year of endangered Shortnose and Lost River Suckers. Host ecologies differed as did parasite infections. Shortnose Suckers were more likely to be caught inshore and 3–5 times more likely to have Bolbophorus spp. and Contracaecum sp. infections, and Lost River Suckers were more likely to be caught offshore and approximately three times more likely to have Lernaea cyprinacea infections. An observed peak shift seems likely to be due to a lower host size limit for Bolbophorus spp. (13.6 mm) compared with L. cyprinacea (23.4 mm). The large data set allowed us to generate strong hypotheses: (i) that a major marsh restoration project had unintended consequences that resulted in an increase in infections; (ii) that co-infection with Bolbophorus spp. increased the odds of infection by L. cyprinacea and Contracaecum sp.; (iii) that significant declines in the odds of infection over approximately 25 days were due to parasite-induced host mortality; (iv) that the fish’s small size relative to L. cyprinacea and Contracaecum sp. might be directly lethal; (v) that the absence of L. cyprinacea infections in the early 1990s was associated with good year-class production of the suckers; and (vi) that parasites might increase the odds of vagrancy from the nursery ground.

Oregon↗

USGS2019

Adaptive management of flows from R.L. Harris Dam (Tallapoosa River, Alabama)—Stakeholder process and use of biological monitoring data for decision making

Adaptive management has been applied to problems with multiple conflicting objectives in various natural resources settings to learn how management actions affect divergent values regarding system response. Hydropower applications have only recently begun to emerge in the field, yet in the specific example reported herein, stakeholders invested in determining the best management alternatives for attainment of a suite of objectives outlined in a long-term adaptive management program below R.L. Harris Dam, a large, privately owned dam in Alabama. Stakeholders convened an objective-setting workshop to engage a governance structure and developed a decision support model to determine appropriate actions that optimized stakeholder values. The process led to implemented change in dam operation inclusive of incorporating hypothetical responses in system parameters to management. To account for the iterative loop of adaptive management, yearly monitoring of state variables that approximated many stakeholder objectives was performed from 2005 to 2016 and data collected were incorporated into the decision model. Specific analysis of fish and macroinvertebrate population responses indicated a less than satisfactory response for some stakeholders to the flow-management changes at the dam. Uncertainty regarding the best management to provide adequate hydrologic and thermal habitats for fauna and boatable days for recreationists still exists. The project led to a Federal Energy Regulatory Commission process for renewing the license to operate the dam (beginning in 2018); adaptive management could be a viable path forward to ensure stakeholder satisfaction related to new management options.

Alabama↗

USGS2019

Disentangling effects of invasive species and habitat while accounting for observer error in a long-term amphibian study

The invasive American bullfrog ( Lithobates catesbeianus ) and a variety of non‐native sport fish commonly co‐occur in lowland lentic habitats of the western United States. Both invasive taxa are implicated in declines of native amphibians in this region, but few long‐term studies of communities exist. Further, field studies of invasive–native interactions are complicated by confounding habitat modifications and observation errors. We surveyed amphibians and measured habitat characteristics for 12 yr across 38 wetland sites within the Willamette Valley, Oregon, USA. We assessed the influence of invasive species, habitat, and their interactions on the distributions of five native amphibian species using a multispecies dynamic occupancy model that accounted for false‐negative and false‐positive detections. In general, habitat characteristics—such as within‐pond vegetation cover, surrounding forest, and drought severity—were important for local persistence of native species when bullfrogs co‐occurred. We also found evidence of a cumulative negative effect of bullfrogs and non‐native fish (families Centrarchidae and Ictaluridae) on northern red‐legged frog ( Rana aurora ) local persistence that was mediated by the dominance of invasive reed canarygrass ( Phalaris arundinacea ). Non‐native fish and bullfrogs had variable effects on native amphibian species, but neither invasive taxon appears to be causing declines in occupied sites within our study area. Moreover, species relationships with habitat differed when invaders were present, indicating that certain habitats may increase persistence of native amphibians in the invaded landscape.

Oregon↗

USGS2018

An evaluation of three fish surveys in the San Francisco Estuary, 1995–2015

Resource managers rely on long-term monitoring surveys conducted in the San Francisco Estuary to evaluate the status and trends of resident fish populations in this important region. These surveys are potentially confounded because of the incomplete detection of individuals and species, the magnitude of which is often related to the same factors that affect fish populations. We used multistate occupancy estimators to evaluate the distribution, abundance, and detection probability of four fish species collected during 1995–2015 with three long-term surveys. Detection probabilities varied positively with fish abundance and negatively with Secchi depth. Detection varied among species and was greatest for the 20-mm Survey and least for the midwater trawl used for the midwater trawl used in the San Francisco Bay Study. Incomplete detection resulted in underestimates of occupancy and abundance across species and surveys and were greatest for the Bay Study. However, trends in occupancy and abundance of the study period appeared to be unbiased. Fish occupancy and abundance were generally related to salinity or specific conductance, day-of-the year, and water temperature, but the nature of the relations varied among surveys and species. There also was strong spatial and temporal dependence in species-specific occupancy and abundance that changed through time and were unrelated to the covariates considered. Our results suggest that managers consider incorporating methods for estimating detection and adjusting data to ensure data quality. Additionally, the strong spatio-temporal patterns in the monitoring data suggest that existing protocols may need to be modified to ensure that data and inferences reflect system-wide changes rather than changes at a specific set of non-randomly selected locations.

California↗

USGS2018

Identifying optimal hauling densities for adult Chinook Salmon trap and haul operations

Trap and haul programs are used to conserve fish populations by circumventing high mortality locations or events, and enhancing population abundance by reintroducing fish to historical habitats and mitigating for fish passage limitations. Spring run Chinook Salmon are transported in trucks upstream of barrier dams in Willamette River Tributaries as part of fish conservation efforts. Fish mortalities occurring during hauling minimizes the utility of the effort because natural origin fish are targeted for theses outplanting efforts. The objectives of this study were to develop models predicting hauling mortality and identify optimal hauling densities that minimize mortality risk and effort. We used an information-theoretic approach to evaluate multiple models predicting hauling mortality. Predictors identified varied between the two dams evaluated but were related to operations and annual or in-river conditions. The amount of time loading fish and the density of fish in tank trucks were positively associated with hauling mortality. Instream flows and thermal exposure were also identified as factors predicting with hauling mortality. We used the results of model selection to predict mortality risk and calculate daily hauling effort. Risk and effort were combined into a utility to identify optimal hauling densities for varying numbers of fish to haul and transport truck volume. Optimal hauling densities varied between dams reflecting whether loading time or hauling density was associated with hauling mortality. This analysis provides managers a way to integrate research, monitoring, and management to improve understanding of factors associated with hauling mortality and adjust optimal hauling densities using adaptive management.

Oregon↗

USGS2018

Fish misidentification and potential implications to monitoring within the San Francisco Estuary, California

Fish monitoring programs often rely on the collection, species identification, and counting of individual fish over time to inform natural resource management decisions. Thus, the utility of the data used to inform these decisions can be negatively affected by species misidentification. Fish species misidentification bias can be minimized by confirming identification using genetic techniques, training observers, or adjusting monitoring data using estimates of incomplete detection and false-positive misidentification. Despite the existence of well-established fish identification training and quality control programs, there is considerable uncertainty about fish species false-positive misidentification rates and the effectiveness of fish identification training programs within the San Francisco Estuary. We evaluated the misidentification of fish species among Delta Juvenile Fish Monitoring Program observers by conducting five fish identification exams under controlled conditions at the Lodi Fish and Wildlife Office in Lodi, California, between 2012 and 2014. To assess the variability in false-positive misidentification, we fitted data to species and observer characteristics using hierarchical logistic regression. We found that fish species misidentification was fairly common, averaging 17% among 155 test specimens and 32 observers. False-positive misidentification varied considerably among species and was negatively related to fish size, the abundance of the species within monitoring samples, and observer experience. In addition, observers who were not formally trained or used as full-time observers were, on average, 6.0 times more likely to falsely identify a species. However, false-positive misidentification rates among observers and specimens still varied considerably after controlling for observer experience and training, and species and size, respectively. Our results could be used to improve fish identification training and testing, increase the accuracy of fish occupancy or abundance estimation, and justify the allocation of resources to continually use and formally train full-time observers within long-term monitoring programs operating in the system.

California↗

USGS2018

The influence of land-cover changes on the variability of saturated hydraulic conductivity in tropical peatlands

Understanding the movement of water through peat is essential for effective conservation and management strategies for peatlands. Saturated hydraulic conductivity, K s , describes water movement through the peat profile. However, the spatial variability of K s in tropical peatlands and the effects of land conversion on peat characteristics are poorly understood. Utilizing the slug test method, we estimated hydraulic conductivity in tropical peatlands in West Kalimantan, Indonesia, at three depths (0.75, 3.5, and 5.5 m) across four different land-cover types (undrained forests, recently burned forests, early seral communities, and oil palm ( Elaeis guineensis Jacq.) plantations). We found strong spatial autocorrelation among measurements collected at our 19 study sites and evaluated the relationship between hydraulic conductivity and land-cover types, peat properties, and depth of measurement with a hierarchical linear model. Hydraulic conductivity varied greatly ( c. 0.001–13.9 m d −1 ). The best approximating model for estimating K s contained depth, forest cover, a depth and forest cover interaction, and the von Post degree of decomposition ( K s ~ depth + forest + depth × forest + von Post). Parameter estimates indicated that K s was greater in forested than non-forested sites and decreased with increasing depth and decomposition stage. There was no evidence that K s differed among the non-forested sites or was related to other physical and chemical peat properties. Our results suggest that K s should be measured directly in tropical peatlands rather than estimated as a function of peat properties. Additionally, the strong spatial dependence suggests that similar research designs should examine the sample data for spatial dependence and, if necessary, incorporate hierarchical models.

Mitigation and Adaption Strategies for Global Chan↗

USGS2018

Multiple drivers, scales, and interactions influence southern Appalachian stream salamander occupancy

Understanding how factors that vary in spatial scale relate to population abundance is vital to forecasting species responses to environmental change. Stream and river ecosystems are inherently hierarchical, potentially resulting in organismal responses to fine‐scale changes in patch characteristics that are conditional on the watershed context. Here, we address how populations of two salamander species are affected by interactions among hierarchical processes operating at different scales within a rapidly changing landscape of the southern Appalachian Mountains. We modeled reach‐level occupancy of larval and adult black‐bellied salamanders ( Desmognathus quadramaculatus ) and larval Blue Ridge two‐lined salamanders ( Eurycea wilderae ) as a function of 17 different terrestrial and aquatic predictor variables that varied in spatial extent. We found that salamander occurrence varied widely among streams within fully forested catchments, but also exhibited species‐specific responses to changes in local conditions. While D. quadramaculatus declined predictably in relation to losses in forest cover, larval occupancy exhibited the strongest negative response to forest loss as well as decreases in elevation. Conversely, occupancy of E. wilderae was unassociated with watershed conditions, only responding negatively to higher proportions of fast‐flowing stream habitat types. Evaluation of hierarchical relationships demonstrated that most fine‐scale variables were closely correlated with broad watershed‐scale variables, suggesting that local reach‐scale factors have relatively smaller effects within the context of the larger landscape. Our results imply that effective management of southern Appalachian stream salamanders must first focus on the larger scale condition of watersheds before management of local‐scale conditions should proceed. Our findings confirm the results of some studies while refuting the results of others, which may indicate that prescriptive recommendations for range‐wide management of species or the application of a single management focus across large geographic areas is inappropriate.

Georgia, North Carolina↗

USGS2018

Fall and winter microhabitat use and suitability for spring chinook salmon parr in a U.S. Pacific Northwest River

Habitat degradation has been implicated as a primary threat to Pacific salmon Oncorhynchus spp. Habitat restoration and conservation are key toward stemming population declines; however, winter microhabitat use and suitability knowledge are lacking for small juvenile salmonids. Our objective was to characterize microhabitat use and suitability for spring Chinook Salmon Oncorhynchus tshawytscha parr during fall and winter. Using radiotelemetry techniques during October–February (2009–2011), we identified fall and winter microhabitat use by spring Chinook Salmon parr in Catherine Creek, northeastern Oregon. Tagged fish occupied two distinct gradient reaches (moderate and low). Using a mixed‐effects logistic regression resource selection function (RSF) model, we found evidence that microhabitat use was similar between free‐flowing and surface ice conditions. However, habitat use shifted between seasons; most notably, there was greater use of silt substrate and areas farther from the bank during winter. Between gradients, microhabitat use differed with greater use of large wood (LW) and submerged aquatic vegetation in the low‐gradient reach. Using a Bayesian RSF approach, we developed gradient‐specific habitat suitability criteria. Throughout the study area, deep depths and slow currents were most suitable, with the exception of the low‐gradient reach where moderate depths were optimal. Near‐cover coarse and fine substrates were most suitable in the moderate‐ and low‐gradient reaches, respectively. Near‐bank LW was most suitable throughout the study area. Multivariate principal component analyses (PCA) indicated co‐occurring deep depths supporting slow currents near cover were intensively occupied in the moderate‐gradient reach. In the low‐gradient reach, PCA indicated co‐occurring moderate depths, slow currents, and near‐bank cover were most frequently occupied. Our study identified suitable and interrelated microhabitat combinations that can guide habitat restoration for fall migrant and overwintering Chinook Salmon parr in Catherine Creek and potentially the Pacific Northwest.

Oregon↗

USGS2018

Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches

Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision making. Therefore, we also discuss alternative approaches to yield unbiased estimates of population state variables using similar data types, and we stress that there is no substitute for an effective sample design that is grounded upon well-defined management objectives.

Ecological Modelling↗

USGS2018

Evaluating trade-offs in bull trout reintroduction strategies using structured decision making

Structured decision making allows reintroduction decisions to be made despite uncertainty by linking reintroduction goals with alternative management actions through predictive models of ecological processes. We developed a decision model to evaluate the trade-offs between six bull trout ( Salvelinus confluentus ) reintroduction decisions with the goal of maximizing the number of adults in the recipient population without reducing the donor population to an unacceptable level. Sensitivity analyses suggested that the decision identity and outcome were most influenced by survival parameters that result in increased adult abundance in the recipient population, increased juvenile survival in the donor and recipient populations, adult fecundity rates, and sex ratio. The decision was least sensitive to survival parameters associated with the captive-reared population, the effect of naivety on released individuals, and juvenile carrying capacity of the reintroduced population. The model and sensitivity analyses can serve as the foundation for formal adaptive management and improved effectiveness, efficiency, and transparency of bull trout reintroduction decisions.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2017

Rearing environment influences boldness and prey acquisition behavior, and brain and lens development of bull trout

Animals reared in barren captive environments exhibit different developmental trajectories and behaviors than wild counterparts. Hence, the captive phenotypes may influence the success of reintroduction and recovery programs for threatened and endangered species. We collected wild bull trout embryos from the Metolius River Basin, Oregon and reared them in differing environments to better understand how captivity affects the bull trout Salvelinus confluentus phenotype. We compared the boldness and prey acquisition behaviors and development of the brain and eye lens of bull trout reared in conventional barren and more structurally complex captive environments with that of wild fish. Wild fish and captive reared fish from complex habitats exhibited a greater level of boldness and prey acquisition ability, than fish reared in conventional captive environments. In addition, the eye lens of conventionally reared bull trout was larger than complex reared captive fish or same age wild fish. Interestingly, we detected wild fish had a smaller relative cerebellum than either captive reared treatment. Our results suggest that rearing fish in more complex captive environments can create a more wild-like phenotype than conventional rearing practices. A better understanding of the effects of captivity on the development and behavior of bull trout can inform rearing and reintroduction programs though prediction of the performance of released individuals.

Environmental Biology of Fishes↗

USGS2017

A new parameterization for integrated population models to document amphibian reintroductions

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog ( Rana pretiosa ) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010–2011 to 0.86 in 2012–2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but related, data sets has an advantage of being able to estimate complex ecological relationships across multiple life stages, offering a modeling framework that accommodates uncertainty, enforces parsimony, and ensures all model parameters can be confronted with monitoring data.

Ecological Applications↗