Geology topics

Adam Duarte

Publications and source records attributed to Adam Duarte.

At least 19 recordsLinked to original sources

USGS2026

Avoiding common pitfalls in the implementation of adaptive forest wildlife management

Forest management planning requires the evaluation of tradeoffs in proposed management actions to meet multiple objectives, including providing the habitat required to sustain wildlife populations. However, various species-specific life history strategies and ecological uncertainties complicate our understanding of the responses of wildlife to disturbances, such as wildfires and forest management. We believe that adaptive management processes, applied through the close collaboration of researchers and managers (e.g., coproduction), will be valuable in this effort. Although adaptive management programs have been touted in the past, we stress that many of these programs have fallen short of the requisite steps to complete the learning cycles of this process (i.e., single- and double-loop learning). Thus, we provide guidance on what we believe to be the missing components of these efforts in hopes to guide future coordination of local and regional adaptive management programs for forest wildlife.

General Technical Report↗

USGS2025

Passive acoustic monitoring is a cost-effective approach to conduct inland surveys for marbled murrelets

The marbled murrelet ( Brachyramphus marmoratus ) is a seabird of conservation concern that nests in late-successional, old-growth forests in Oregon, Washington, and California, USA. Traditional audio-visual surveys have been the standard method for detecting murrelets in forests. Given that murrelets can be extremely cryptic in forest environments, audio-visual surveys are difficult, time consuming, and expensive to conduct. Passive acoustic monitoring (PAM) may be a useful and cost-effective alternative. Using a paired murrelet survey design, we compared detection probabilities across 88 survey points in forests of Oregon and Washington. We conducted 2–4 early morning audio-visual surveys and 13–53-day PAM surveys from 14 June through 5 August 2022 and 2023, when murrelets typically make the most frequent inland flights during the nesting season. We found the average detection probability for murrelets on any given day was higher for an audio-visual survey visit (0.40, SD = 0.17) than for a PAM survey day (0.19, SD = 0.10). However, the cumulative detection probability for PAM surveys was 0.98 (95% CI = 0.96–1.0) after 19 survey days, whereas the same cumulative detection probability would require 9 audio-visual survey visits. Using simulations to compare the cost-effectiveness of both methods, we found audio-visual surveys cost more when compared with PAM surveys in 61–91% of scenarios because they require specialized personnel training and additional pre-dawn visits. Further, PAM per survey costs decreased as the number of survey days per point increased and over time after initial costs were incurred, particularly when autonomous recording units were reused for multiple years. While audio-visual surveys are the standard method for murrelet surveys in forest habitats, PAM represents a more cost-effective approach to determine the presence of murrelets.

Oregon, Washington↗

USGS2025

Simulated soundscapes and transfer learning boost the performance of acoustic classifiers under data scarcity

1. The biodiversity crisis necessitates spatially extensive methods to monitor multiple taxonomic groups for evidence of change in response to evolving environmental conditions. Programs that combine passive acoustic monitoring and machine learning are increasingly used to meet this need. These methods require large, annotated datasets, which are time-consuming and expensive to produce, creating potential barriers to adoption in data- and funding-poor regions. Recently released pre-trained avian acoustic classification models provide opportunities to reduce the need for manual labelling and accelerate the development of new acoustic classification algorithms through transfer learning. Transfer learning is a strategy for developing algorithms under data scarcity that uses pre-trained models from related tasks to adapt to new tasks. 2. Our primary objective was to develop a transfer learning strategy using the feature embeddings of a pre-trained avian classification model to train custom acoustic classification models in data-scarce contexts. We used three annotated avian acoustic datasets to test whether transfer learning and soundscape simulation-based data augmentation could substantially reduce the annotated training data necessary to develop performant custom acoustic classifiers. We also conducted a sensitivity analysis for hyperparameter choice and model architecture. We then assessed the generalizability of our strategy to increasingly novel non-avian classification tasks. 3. With as few as two training examples per class, our soundscape simulation data augmentation approach consistently yielded new classifiers with improved performance relative to the pre-trained classification model and transfer learning classifiers trained with other augmentation approaches. Performance increases were evident for three avian test datasets, including single-class and multi-label contexts. We observed that the relative performance among our data augmentation approaches varied for the avian datasets and nearly converged for one dataset when we included more training examples. 4. We demonstrate an efficient approach to developing new acoustic classifiers leveraging open-source sound repositories and pre-trained networks to reduce manual labelling. With very few examples, our soundscape simulation approach to data augmentation yielded classifiers with performance equivalent to those trained with many more examples, showing it is possible to reduce manual label-ling while still achieving high-performance classifiers and, in turn, expanding the potential for passive acoustic monitoring to address rising biodiversity monitoring needs.

Methods in Ecology and Evolution↗

USGS2024

Invisible hand of sampling for management: Underlying needs to survey a threatened seabird can bias aggregated data

Aim Surveying for a species of concern ahead of proposed activities that alter its habitat is routine practice in conservation and management. Such surveys may accumulate large datasets that could further elucidate trends in abundance and distribution. However, the as-needed surveying of proposed activities may impart a sample site selection bias on the data if used for another purpose. Management of a threatened, forest-nesting seabird offered an example of this. Here we assessed how resource management planning and survey requirements can bias clearance monitoring survey data collected prior to proposed timber harvests, if those data are used for other purposes. Location Oregon and Washington, USA. Taxon Marbled Murrelet ( Brachyramphus marmoratus ). Methods To assess how timber planning and other factors influenced marbled murrelet survey location selection, we used logistic regression models to examine habitat associations of marbled murrelet survey sites ( n = 9178) encompassing proposed timber harvests, and the survey stations ( n = 38,923) therein, across the murrelet's inland range in Washington and Oregon, USA between 1989 and 2021. We then simulated the effect this selective sampling might have on assessments of occupancy trends. Results Most habitat characteristics considered did influence where surveys were located, with distance to roads often being the strongest predictor of survey location. The strength of selection for each covariate changed over time, such that a habitat characteristic strongly influenced location selection in a year but was less influential in another year. The simulation analysis suggested that the non-random selection of survey sites could profoundly bias assessments of occupancy trends. Conclusions When using these clearance monitoring survey data– or any data–beyond their original purpose, careful consideration should be given to the scope of inference provided and analytical methods used, to ensure that observed trends are the product of biological processes and not biased by sampling artefacts.

Oregon, Washington↗

USGS2024

Bayesian networks facilitate updating of species distribution and habitat suitability models

Managers often rely on predictions of species distributions and habitat suitability to inform conservation and management decisions. Although numerous approaches are available to develop models to make these predictions, few approaches exist to update existing models as new data accumulate. There is a need for updatable models to ensure good modeling practices in an aim to keep pace with change in the environment and change in data availability to continue to use the best-available science to inform decisions. We demonstrated a workflow to deliver predictive models to user groups within Bayesian networks, allowing models to be used to make predictions across new sites and to be easily updated with new data. To demonstrate this workflow, we focus on species distribution and habitat suitability models given their importance to informing conservation strategies across the globe. In particular, we followed a standard process of collating species encounter data available in online databases and ancillary covariate data to develop a habitat suitability model. We then used this model to parameterize a Bayesian network and updated the model with new data to predict species presence in a new focal ecoregion. We found the network updated relatively quickly as new data were incorporated, and the overall error rate generally decreased with each model update. Our approach allows for the formal incorporation of new data into predictions to help ensure model predictions are based on all relevant data available, regardless of whether they were collected after initial model development. Although our focus is on species distribution and habitat suitability models to inform conservation efforts, the workflow we describe herein can easily be applied to any use case where model uncertainty reduction and increased model prediction accuracy are desired via model updating as new data become available. Thus, our paper describes a generalizable workflow to implement model updating, which is widely recognized as a good modeling practice but is also underutilized in applied ecology.

Oregon, Washington↗

USGS2024

An integrated analysis for estimation of survival, growth, and movement of unmarked juvenile anadromous fish

Managers invest substantial resources to promote recovery of declining anadromous fish stocks. Recovery strategies are manifold and often include management actions intended to stimulate somatic growth, increase in-river survival, and motivate juvenile outmigration during favorable environmental conditions. Evaluating the efficacy of these management actions is difficult, however, because monitoring data that explicitly track individuals from egg deposition to juvenile outmigration are typically lacking. We developed an integrated population model that links two different and often collected types of anadromous fish monitoring data: spawning ground surveys and rotary screw trap juvenile catch data. The integrated model accounts for incomplete detection and uses the two sources of data to estimate juvenile demographic parameters in a multistate framework. We evaluated the model's performance using simulated data under a range of conditions typically encountered in similar surveys. Simulation results indicated that the model estimated juvenile survival, growth, and movement with no-to-minimal bias (i.e., ≥ 50 % of simulations ± 0–0.05). As an example case study, we fit the model to empirical fall-run Chinook Salmon ( Oncorhynchus tshawytscha ) monitoring data collected in California's Central Valley, U.S.A. In doing so, we evaluated the influence of environmental conditions (e.g., discharge, water temperature) and habitat availability on juvenile demographic rates. We demonstrated that through our integrated approach we could estimate state transition probabilities that are typically inestimable for naturally produced, unmarked juvenile fish when using traditional statistical approaches to analyze these types of monitoring data. Furthermore, the structure of our model can serve as a useful foundation for decision-support models within adaptive management programs by directly linking management actions, decision-support-model predictions, and monitoring.

California↗

USGS2024

An evaluation of tradeoffs in restoring ephemeral vs. perennial habitats to conserve animal populations

Introduction: Habitat loss and degradation pose significant threats to global fish and wildlife populations, prompting substantial investments in habitat creation and restoration efforts. Not all habitats provide equal benefits, leading to challenges in prioritizing restoration actions. For example, juvenile anadromous salmonids require high quality rearing aquatic habitats to achieve the physiological requirements needed to successfully migrate to the ocean. However, there are profound disagreements among anadromous salmon restoration managers whether it is best to focus efforts on restoring in-channel habitats that are available for the entire rearing period or floodplain habitats that, while facilitating greater growth and survival than in-channel habitats, are only available for a few weeks at a time and are typically only activated every two-to-three years. Methods: We used an existing fall-run Chinook salmon decision-support model to evaluate under what conditions floodplain restoration would provide greater benefits than in-channel habitat restoration. The simulations included a wide range of floodplain inundation frequencies and durations and floodplain benefits in the form of increased survival and growth relative to in-channel habitats. Results: The simulations results indicated that in-channel habitat restoration was always the best habitat restoration action when there was no existing in-channel habitat despite simulating a wide range of flood frequency, duration, and growth and survival benefits. Floodplain restoration was generally best when there was sufficient in-channel habitat available to successfully rear most of the juveniles produced by the returning adult salmon. Discussion: We hypothesize that in-channel and floodplain habitats have different roles in salmon population maintenance with in-channel habitats regulating the overall population size and floodplains acting as recurrent resource pulses. Our study provides a quantitative framework to evaluate the benefit of these two habitat types and provides generalizable rulesets that can be used by managers when implementing habitat restoration strategies for species that inhabit both in-channel and floodplain habitats.

California↗

USGS2024

Passive acoustic monitoring and convolutional neural networks facilitate high-resolution and broadscale monitoring of a threatened species

Population monitoring is an essential component of biodiversity conservation and management, but low detection probabilities for rare and/or cryptic species makes estimating abundance and occupancy challenging. Passive acoustic monitoring combined with machine learning algorithms represents a potential path forward to effectively and efficiently monitor the occurrence of rare vocalizing species across entire forest landscapes. Our objectives were to develop and implement a convolutional neural network (PNW-Cnet) to identify vocalizations of a rare and threatened forest nesting bird species – the marbled murrelet ( Brachyramphus marmoratus ) – in the Pacific Northwest, U.S.A., 2018–2021. We used PNW-Cnet predictions from broadscale passive acoustic monitoring data to examine spatiotemporal patterns in the distribution of murrelets. PNW-Cnet showed sufficiently high prediction accuracy (overall precision > 0.9) to enable broadscale population monitoring. Spatiotemporal analysis showed that annual peak murrelet call abundance occurs in ordinal weeks 28–32 (late July–Mid August) but this varied by study area. The greatest number of detections typically occurred in the Olympic Peninsula and Oregon Coast Range where late-successional forest dominates and nearer to ocean habitats. We demonstrate that passive acoustic monitoring can be used to understand intensity of use across broad scales for a rare and cryptic species in addition to the typical detection/non-detection data that are often collected. Passive acoustic monitoring combined with PNW-Cnet offers considerable promise for species distribution modeling and long-term population monitoring for rare species.

Oregon, Washington↗

USGS2024

Prototyping structured decision making for water resource management in the San Francisco Bay-Delta

A structured decision making (SDM) approach can help evaluate tradeoffs between conservation and human-benefit objectives by fostering communication and knowledge transfer among stakeholders, decision makers, and the public. However, the process is iterative and completing the full process may take years. It can be difficult to initiate an SDM effort when problems seem insurmountable. Occasionally, SDM may not even be the best or correct approach for addressing the conservation problem at hand. We describe the implementation of an SDM process to help inform difficult decisions related to competing objectives. We convened a diverse stakeholder group from the largest estuary in the western United States; the San Francisco Bay and Sacramento-San Joaquin Delta (Bay-Delta). The stakeholder group consisted of representatives from local, state, and federal agencies, non-profit organizations, and recreational fishers. The stakeholder group agreed on a problem statement and identified four priority objectives related to Chinook salmon, delta smelt, water availability and reliability, and agricultural water use. Furthermore, they proposed 14 candidate management actions to achieve their objectives. The group then used existing quantitative models and data to evaluate trade-offs in proposed management actions to identify areas of agreement of proposed candidate actions. The clear communication of the problem statement and objectives among the stakeholder group, along with evaluation of tradeoffs and uncertainty via decision-support models suggest that a full SDM approach may work in the Bay-Delta. We further communicate lessons learned during our implementation of SDM to help guide future SDM efforts in the region and elsewhere.

California↗

USGS2024

Habitat use of anadromous and amphidromous sturgeons in North America: A systematic review

Sturgeons are among the most endangered fishes in the world. Identifying habitat use characteristics to inform restoration projects is crucial for recovery. However, small sample sizes, inadequate replication of studies, and limited spatial extents complicate our ability to effectively apply the findings of single studies to endangered species conservation across the larger riverscape. We synthesized information from amphidromous and anadromous sturgeons in North America to identify species-specific knowledge gaps and conduct a quantitative comparison of species–habitat relationships. We provided a qualitative summary of substrate use and synthesized estimates of depth and velocity during spawning and non-spawning activity. Generalized patterns among species were identified, such as spawning in fast water on hard substrate and then using slow water with soft substrate areas when not spawning. We noted species-specific variability during spawning that may be attributed to historical maximum length, egg characteristics, and watershed features. This study provides some of the first estimates of habitat use that can be adapted for many populations. Results can contribute to empirically grounded decision-support tools used to prioritize information needs for recovery.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2023

Imperfect detection and misidentification affect inferences from data informing water operation decisions

Objective Managers can modify river flow regimes using fish monitoring data to minimize impacts from water management infrastructure. For example, operation of the gate-controlled Delta Cross Channel (DCC) in California can negatively affect the endangered Sacramento River winter-run Chinook Salmon Oncorhynchus tshawytscha . Although guidelines have been developed for DCC operations by using real-time juvenile fish sampling count data, there is uncertainty about how environmental conditions influence fish occupancy and the extent to which those relationships are affected by sampling and identification error. Methods We evaluated the effect of environmental conditions, imperfect detection, and misidentification error on salmon occupancy by analyzing data using hierarchical multistate occupancy models. A total of 14,147 trawl tows and beach seine hauls were conducted on 1058 sampling days between October and December from 1996 to 2019. During these surveys, 2803 juvenile winter-run Chinook Salmon were identified, and approximately 29% of the sampling days had at least one winter-run juvenile detected. Result The probability of misidentifying an individual juvenile winter-run Chinook Salmon in the field was estimated to be 0.056 based on fish identification examinations and genetic sampling. Occupancy varied considerably and was related to flow characteristics, water clarity, weather, time of year, and whether occupancy was detected during the previous sampling day. However, these relationships and their significance changed considerably when accounting for imperfect detection and the probability of misidentifying individual juvenile salmon. Detection was <0.3 under average sampling conditions during a single sample and was influenced by flow, water clarity, site, and volume sampled. Conclusion Our modeling results indicate that DCC gate closure decisions could occur on fewer days when imperfect detection and misidentification error are not accounted for. These findings demonstrate the need to account for identification and detection error while using monitoring data to assess factors influencing fish occupancy and inform future management decisions.

North American Journal of Fisheries Management↗

USGS2023

Population dynamics of the threatened Oregon spotted frog before and after drought mitigation

Amphibians are among the most sensitive taxa to climate change, and species inhabiting arid and semiarid landscapes at the extremes of their range are especially vulnerable to drought. The Jack Creek, Oregon, USA, population of Oregon spotted frogs ( Rana pretiosa ) faces unique challenges because it occupies the highest elevation site in the species' extant range and one that has been transformed by loss of American beavers ( Castor canadensis ), which historically maintained open water. We evaluated the effects of drought mitigation (addition of excavated ponds) on relationships between local and regional water availability, inactive legacy beaver dams, and Oregon spotted frog population dynamics in the Jack Creek system. We conducted egg mass surveys and capture-mark-recapture sampling at a treatment reach with excavated ponds and 3 reference reaches over 13 years; surveys spanned a period before and after pond excavation at the treatment and 1 primary comparison reference reach. We analyzed data using a combination of robust design capture-mark-recapture estimators and generalized linear mixed models to characterize population dynamics. Adult Oregon spotted frog survival was approximately 19.5% higher at the treatment reach than the primary reference reach during the study period. Annual survival was most strongly associated with late summer vegetation greenness, a proxy for water availability, and males had higher survival than females. Among the 4 study reaches, the treatment reach consistently had higher late summer vegetation greenness, and the hydrology functioned more independently of regional precipitation patterns relative to the reference reaches; however, these dynamics were not linked to pond excavation. Breeding was concentrated in 2 legacy beaver ponds that were deepened by excavation during the study compared to an unexcavated beaver pond, 2 excavated ponds without legacy beaver dams, and 9 reference ponds. These results point to the benefit of enhancing existing beaver structures and indicate that management actions aimed at maintaining surface water for breeding in spring and saturated soils and ponded water for adults in late summer would benefit this unique population of Oregon spotted frogs in the face of drought.

Oregon↗

USGS2023

An evaluation of multistate occupancy models for estimating relative abundance and population trends

Detecting spatiotemporal changes in the abundances of organisms is key to effectively conserving species. While indices of abundance have long been used, there has been a shift toward model-based estimators that account for the detection process. Popular approaches including traditional occupancy models and N-mixture models entail tradeoffs. The traditional occupancy approach requires the researcher coarsen the characterization of abundance to the probability that a site is occupied or unoccupied. Conversely, N-mixture models make use of variation in counts, but perform poorly when individuals have low detectability or move into or out of sites between visits. Multistate occupancy models that differentiate relatively abundant from non-abundant states have the potential to fill this gap but have been underexplored. We conducted a simulation study to test whether multistate occupancy models could capture spatial abundance patterns and detect population declines in the face of low individual detection probability ( p ≤ 0.3) and unmodeled heterogeneity (e.g., that arising from individual movement). We considered 10,773 scenarios to examine the effects of differing amounts of heterogeneity as well as alternative study designs, population parameters, and modeling choices. We tracked bias in the proportion of sites estimated to be in the abundant state for single-season models, and power to detect a declining trend across multiple years. We also evaluated data diagnostic metrics to provide guidance to users. Multistate occupancy models were able to differentiate sites with higher abundances from sites with lower abundances when there were at least medium levels of spatial heterogeneity in true abundances. If different sites were randomly selected each year, power to detect even large population declines (65%) was poor (power < 0.8). However, if the same sites were surveyed each year, and a dynamic multistate occupancy was used, multistate occupancy models could detect (power ≥ 0.8) relatively small declines (5-40%) in 20% of scenarios, and frequently detect large declines of 45-60% (mean power = 0.92). Conservation decisions rely on detecting change reliably, rarely needing absolute abundance information. Multistate occupancy models can improve our ability to detect changing abundance while accommodating low individual detection probability and heterogeneity in count monitoring data.

Ecological Modelling↗

USGS2023

Adjacent and downstream effects of forest harvest on the distribution and abundance of larval headwater stream amphibians in the Oregon Coast Range

Forest harvest is a primary landscape-scale management action affecting riparian forests. Although concerns about impacts of forest harvest on stream amphibians is generally limited to areas adjacent to harvest, there is a paucity of information regarding potential downstream effects of forest harvest on these species. We designed a before-after, control-impact (BACI) experiment to quantify potential impacts of clearcut logging that included 12-m buffers or smaller variable-width buffers on the distribution and abundance of headwater stream amphibians in adjacent and downstream areas. We sampled larval coastal tailed frogs ( Ascaphus truei ), coastal giant salamanders ( Dicamptodon tenebrosus ), and Columbia torrent salamanders ( Rhyacotriton kezeri ) across 3,915 sampling occasions that spanned 13 study reaches in 2008–2011 (pre-harvest) and 2013–2016 (post-harvest) as part of the Trask River Watershed Study in the Oregon Coast Range, U.S.A. We analyzed these data using occupancy models to estimate occupancy and (when possible) relative abundance, while accounting for various sources of imperfect detection. All species exhibited reduced occupancy adjacent to clearcuts with variable-width buffers (odds ratios [ORs] ranged = 0.24–0.48), and these negative impacts were not always diminished when increasing the buffer size to 12 m (ORs ranged = 0.20–3.56). Dicamptodon tenebrosus was the only species to have occupancy impacted in downstream areas, and this negative impact was related to clearcut logging with uniform 12-m buffers (OR = 0.60). This species was also the only species to have abundance negatively impacted by forest harvest in downstream areas (OR = 0.41 with uniform 12-m buffers, OR = 0.38 with variable-width buffers), albeit impacts to abundance were not evaluated for R. kezeri . Ascaphus truei abundance increased in areas downstream of clearcut logging with uniform 12-m buffers (OR = 2.92). Although we found the direction and magnitude of responses varied by species, our study confirms that clearcut logging can have negative impacts on amphibians that inhabit the adjacent stream areas. Perhaps more importantly, we also found that forest harvest can have negative effects on stream amphibians downstream of the harvested area and that increasing the buffer size to 12 m did not necessarily diminish these impacts in adjacent and downstream areas. Altogether, our study provides a nuanced picture of adjacent and downstream effects of forest harvest on three endemic headwater stream amphibians, and our findings demonstrate that forest management practices should consider downstream effects on aquatic taxa when assessing the impact of harvesting trees near headwater streams.

Oregon↗

USGS2022

Integrating monitoring and optimization modeling to inform flow decisions for Chinook salmon smolts

Monitoring is usually among the first actions taken to help inform recovery planning for declining species, but these data are rarely used formally to inform conservation decision making. For example, Central Valley Chinook salmon were once abundant, but anthropogenic activities have led to widespread habitat loss and degradation resulting in significant population declines. Monitoring data suggest survival through the southern Sacramento-San Joaquin River Delta, in particular, may be a limiting factor for juvenile Chinook salmon outmigrating from the San Joaquin River and its tributaries. However, survival and routing monitoring data have not been formally used to inform water management in a decision analytic framework. Here, we illustrate how estimates derived from disjunct monitoring data can be used to inform water management and as a basis for adaptively managing flows. We aggregated a meta-analysis of Chinook salmon smolt survival and routing estimates through the south Delta with other sources of data to develop a survival and routing simulation model to estimate optimal flows for the San Joaquin River during smolt outmigration from February–May. We found that large flow pulses at predictable times during the spring are projected to be optimal for increasing Chinook salmon smolt survival to the San Francisco Bay and that optimal scenarios differed somewhat with water year type. Sensitivity analysis revealed temperature and smolt outmigration timing are driving optimal pulse distribution and that water allocation changes little with parameter uncertainty. This case study highlights the utility of the decision-analytic framework for solving conservation problems.

California↗

USGS2021

Space-for-time is not necessarily a substitution when monitoring the distribution of pelagic fishes in the San Francisco Bay-Delta

Occupancy models are often used to analyze long-term monitoring data to better understand how and why species redistribute across dynamic landscapes while accounting for incomplete capture. However, this approach requires replicate detection/non-detection data at a sample unit and many long-term monitoring programs lack temporal replicate surveys. In such cases, it has been suggested that surveying subunits within a larger sample unit may be an efficient substitution (i.e., space-for-time substitution). Still, the efficacy of fitting occupancy models using a space-for-time substitution has not been fully explored and is likely context dependent. Herein, we fit occupancy models to Delta Smelt ( Hypomesus transpacificus ) and Longfin Smelt ( Spirinchus thaleichthys ) catch data collected by two different monitoring programs that use the same sampling gear in the San Francisco Bay-Delta, USA. We demonstrate how our inferences concerning the distribution of these species changes when using a space-for-time substitution. Specifically, we found the probability that a sample unit was occupied was much greater when using a space-for-time substitution, presumably due to the change in the spatial scale of our inferences. Furthermore, we observed that as the spatial scale of our inferences increased, our ability to detect environmental effects on system dynamics was obscured, which we suspect is related to the tradeoffs associated with spatial grain and extent. Overall, our findings highlight the importance of considering how the unique characteristics of monitoring programs influences inferences, which has broad implications for how to appropriately leverage existing long-term monitoring data to understand the distribution of species.

Calfornia↗

USGS2021

Demography of the Oregon spotted frog along a hydrologically modified river

Altered flow regimes can contribute to dissociation between life history strategies and environmental conditions, leading to reduced persistence reported for many wildlife populations inhabiting regulated rivers. The Oregon spotted frog ( Rana pretiosa ) is a threatened species occurring in floodplains, ponds, and wetlands in the Pacific Northwest with a core range in Oregon, USA. All life stages of R. pretiosa are reliant on aquatic habitats, and inundation patterns across the phenological timeline can have implications for population success. We conducted capture–mark–recapture (CMR) sampling of adult and subadult R. pretiosa at three sites along the Deschutes River downstream from two dams that regulate flows. We related the seasonal extent of inundated habitat at each site to monthly survival probabilities using a robust design CMR model. We also developed matrix projection models to simulate population dynamics into the future under current river flows. Monthly survival was strongly associated with the extent and variability of inundated habitat, suggesting some within-season fluctuations at higher water levels could be beneficial. Seasonal survival was lowest in the winter for all three sites, owing to limited water availability and the greater number of months within this season relative to other seasons. Population growth for the two river-connected sites was most strongly linked to adult survival, whereas population growth at the river-disconnected site was most strongly tied to survival in juvenile stages. This research identifies population effects of seasonally limited water and highlights conservation potential of enhancing survival of particularly influential life stages.

Oregon↗

USGS2021

An updated assessment of status and trend in the distribution of the Cascades frog (Rana cascadae) in Oregon, USA

Conservation efforts need reliable information concerning the status of a species and their trends to help identify which species are in most need of assistance. We completed a comparative evaluation of the occurrence of breeding for Cascades Frog ( Rana cascadae ), an amphibian that is being considered for federal protection under the U.S. Endangered Species Act. Specifically, in 2018–2019 we resurveyed 67 sites that were surveyed approximately 15 y prior and fit occupancy models to quantify the distribution of R. cascadae breeding in the Cascade Range, Oregon, USA. Furthermore, we conducted a simulation exercise to assess the power of sampling designs to detect declines in R. cascadae breeding at these sites. Our analysis of field data combined with our simulation results suggests that if there was a decline in the proportion of sites used for R. cascadae breeding in Oregon, it was likely a < 20% decline across our study period. Our results confirm that while R. cascadae detection probabilities are high, methods that allow the sampling process to be explicitly modeled are necessary to reliably track the status of the species. This study demonstrates the usefulness of investing in baseline information and data quality standards to increase capacity to make similar comparisons for other species in a timeframe that meet the needs of land managers and policy makers.

Oregon↗