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USGS2019

Bioclimatic envelopes for individual demographic events driven by extremes: Plant mortality from drought and warming

The occurrence of plant species across the globe is largely constrained by climate. Ecologists use plant-climate relationships such as bioclimatic envelopes and related niche models to determine potential environmental conditions promoting probable species occurrence. Traditionally bioclimatic envelopes either exclude disturbance explicitly, or only include disturbance as infrequent and smaller scale processes, assuming that the net effect of climate parameters on key demographic processes predict longer-term equilibrial responses of biota. Due to increasing frequency and extent of extreme events associated with climate change, ecologists may need to increase focus on individual demographic events driven by environmental extremes such as widespread coral bleaching or large-scale tree die-off. An expanded focus on how extreme events catalyze individual demographic events would complement existing tools that predict long-term equilibrial biogeographic responses associated with long-term trends in climate. In many cases, extreme conditions (e.g. drought) are a necessary precursor for an abrupt demographic event (e.g. large-scale tree die-off) and the effects of extremes can be exacerbated by climatic trends (e.g. higher temperatures in combination with drought). Here, we highlight application of bioclimatic models for predicting individual demographic events. Defining the environmental conditions that precipitate demographic events such as widespread tree mortality is a necessary precursor for applying predictions to geographic space, and may require challenging biota with experiments that impose a combination of ecologically extreme conditions in one parameter and a shifting distribution in another (e.g. drought under higher temperatures). Currently data on conditions that drive individual demographic events associated with extremes are usually rare, aggregated across time, and/or correlative. We highlight this approach with a case study of drought-induced mortality in adult Pinus edulis trees that predicts a more than five-fold increase in frequency of die-off events under a global change scenario of high emissions. This general approach complements both traditional bioclimatic envelopes and more detailed physiological approaches currently being refined to address climate change challenges. Notably, this proposed approach could be developed for any climate condition or plant life stage, offering promise for improving predictions of individual demographic events that are rapidly altering ecosystems globally.

International Journal of Plant Sciences↗

USGS2022

Estimating allowable take for an increasing bald eagle population in the United States

Effectively managing take of wildlife resulting from human activities poses a major challenge for applied conservation. Demographic data essential to decisions regarding take are often expensive to collect and are either not available or based on limited studies for many species. Therefore, modeling approaches that efficiently integrate available information are important to improving the scientific basis for sustainable take thresholds. We used the prescribed take level (PTL) framework to estimate allowable take for bald eagles ( Haliaeetus leucocephalus ) in the conterminous United States. We developed an integrated population model (IPM) that incorporates multiple sources of information and then use the model output as the scientific basis for components of the PTL framework. Our IPM is structured to identify key parameters needed for the PTL and to quantify uncertainties in those parameters at the scale at which the United States Fish and Wildlife Service manages take. Our IPM indicated that mean survival of birds >1 year old was high and precise (0.91, 95% CI = 0.90–0.92), whereas mean survival of first-year eagles was lower and more variable (0.69, 95% CI = 0.62–0.78). We assumed that density dependence influenced recruitment by affecting the probability of breeding, which was highly imprecise and estimated to have declined from approximately 0.988 (95% CI = 0.985–0.993) to 0.66 (95% CI = 0.34–0.99) between 1994 and 2018. We sampled values from the posterior distributions of the IPM for use in the PTL and estimated that allowable take (e.g., permitted take for energy development, incidental collisions with human made structures, or removal of nests for development) ranged from approximately 12,000 to 20,000 individual eagles depending on risk tolerance and form of density dependence at the scale of the conterminous United States excluding the Southwest. Model-based thresholds for allowable take can be inaccurate if the assumptions of the underlying framework are not met, if the influence of permitted take is under-estimated, or if undetected population declines occur from other sources. Continued monitoring and use of the IPM and PTL frameworks to identify key uncertainties in bald eagle population dynamics and management of allowable take can mitigate this potential bias, especially where improved information could reduce the risk of permitting non-sustainable take.

Journal of Wildlife Management↗

USGS2001

Three-dimenstional crustal velocity structure beneath the Strait of Georgia, British Columbia

The Strait of Georgia is a topographic depression straddling the boundary between the Insular and Coast belts in southwestern British Columbia. Two shallow earthquakes located within the strait ( M = 4.6 in 1997 and M = 5.0 in 1975) and felt throughout the Vancouver area illustrate the seismic potential of this region. As part of the 1998 Seismic Hazards Investigation of Puget Sound (SHIPS) experiment, seismic instruments were placed in and around the Strait of Georgia to record shots from a marine source within the strait. We apply a tomographic inversion procedure to first-arrival traveltime data to derive a minimum-structure 3-D P -wave velocity model for the upper crust to about 13 km depth. We also present a 2-D velocity model for a profile orientated across the Strait of Georgia derived using a minimum-parameter traveltime inversion approach. This paper represents the first detailed look at crustal velocity variations within the major Cretaceous to Cenozoic Georgia Basin, which underlies the Strait of Georgia. The 3-D velocity model clearly delineates the structure of the Georgia Basin. Taking the 6 km s −1 isovelocity contour to represent the top of the underlying basement, the basin thickens from between 2 and 4 km in the northwestern half of the strait to between 8 and 9 km at the southeastern end of the study region. Basin velocities in the northeastern half are 4.5–6 km s −1 and primarily represent the Upper Cretaceous Nanaimo Group. Velocities to the south are lower (3–6 km s −1 ) because of the additional presence of the overlying Tertiary Huntingdon Formation and more recent sediments, including glacial and modern Fraser River deposits. In contrast to the relatively smoothly varying velocity structure of the basin, velocities of the basement rocks, which comprise primarily Palaeozoic to Jurassic rocks of the Wrangellia Terrane and possibly Jurassic to mid-Cretaceous granitic rocks of the Coast Belt, show significantly more structure, probably an indication of the varying basement rock lithologies. The 2-D velocity model more clearly reveals the velocity layering associated with the recent sediments, Huntingdon Formation and Nanaimo Group of the southern Georgia Basin, as well as the underlying basement. We interpret lateral variation in sub-basin velocities of the 2-D model as a transition from Wrangellian to Coast Belt basement rocks. The effect of the narrow, onshore–offshore recording geometry of the seismic experiment on model resolution was tested to allow a critical assessment of the validity of the 3-D velocity model. Lateral resolution throughout the model to a depth of 3–5 km below the top of the basement is generally 10–20 km.

British Columbia↗

USGS2007

Quantifying the impact of longline fisheries on adult survival in the black-footed albatross

1. Industrial longline fishing has been suspected to impact upon black-footed albatross populations Phoebastria nigripes by increasing mortality, but no precise estimates of bycatch mortality are available to ascertain this statement. We present a general framework for quantifying the relationship between albatross population and longline fishing in absence of reliable estimates of bycatch rate. 2. We analysed capture-recapture data of a population of black-footed albatross to obtain estimates of survival probability for this population using several alternative models to adequately take into account heterogeneity in the recapture process. Instead of trying to estimate the number of birds killed by using various extrapolations and unchecked assumptions, we investigate the potential relationship between annual adult survival and several measures of fishing effort. Although we considered a large number of covariates, we used principal component analysis to generate a few uncorrelated synthetic variables from the set and thus we maintained both power and robustness. 3. The average survival for 1997-2002 was 92%, a low value compared to estimates available for other albatross species. We found that one of the synthetic variables used to summarize industrial longline fishing significantly explained more than 40% of the variation in adult survival over 11 years, suggesting an impact by longline fishing on albatross' survival. 4. Our analysis provides some evidence of non-linear variation in survival with fishing effort. This could indicate that below a certain level of fishing effort, deaths due to incidental catch can be partially or totally compensated for by a decrease in natural mortality. Another possible explanation is the existence of a strong interspecific competition for accessing the baits, reducing the risk of being accidentally hooked. 5. Synthesis and applications . The suspicion of a significant impact of longline fishing on the black-footed albatross population was supported by the combination of a low estimate of adult survival for the study period, and a significant relationship between adult survival and a synthetic measure of fishing effort. This study highlights the sensitivity of the black-footed albatross to commercial longline fishing, and should exhort fishery management authorities to find adequate seabirds avoidance methods and to encourage their employment.

Journal of Applied Ecology↗

USGS2017

Prediction and visualization of redox conditions in the groundwater of Central Valley, California

Regional-scale, three-dimensional continuous probability models, were constructed for aspects of redox conditions in the groundwater system of the Central Valley, California. These models yield grids depicting the probability that groundwater in a particular location will have dissolved oxygen (DO) concentrations less than selected threshold values representing anoxic groundwater conditions, or will have dissolved manganese (Mn) concentrations greater than selected threshold values representing secondary drinking water-quality contaminant levels (SMCL) and health-based screening levels (HBSL). The probability models were constrained by the alluvial boundary of the Central Valley to a depth of approximately 300 m. Probability distribution grids can be extracted from the 3-D models at any desired depth, and are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions. Models were constructed using a Boosted Regression Trees (BRT) machine learning technique that produces many trees as part of an additive model and has the ability to handle many variables, automatically incorporate interactions, and is resistant to collinearity. Machine learning methods for statistical prediction are becoming increasing popular in that they do not require assumptions associated with traditional hypothesis testing. Models were constructed using measured dissolved oxygen and manganese concentrations sampled from 2767 wells within the alluvial boundary of the Central Valley, and over 60 explanatory variables representing regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrologic properties. Models were trained on a USGS dataset of 932 wells, and evaluated on an independent hold-out dataset of 1835 wells from the California Division of Drinking Water. We used cross-validation to assess the predictive performance of models of varying complexity, as a basis for selecting final models. Trained models were applied to cross-validation testing data and a separate hold-out dataset to evaluate model predictive performance by emphasizing three model metrics of fit: Kappa; accuracy; and the area under the receiver operator characteristic curve (ROC). The final trained models were used for mapping predictions at discrete depths to a depth of 304.8 m. Trained DO and Mn models had accuracies of 86–100%, Kappa values of 0.69–0.99, and ROC values of 0.92–1.0. Model accuracies for cross-validation testing datasets were 82–95% and ROC values were 0.87–0.91, indicating good predictive performance. Kappas for the cross-validation testing dataset were 0.30–0.69, indicating fair to substantial agreement between testing observations and model predictions. Hold-out data were available for the manganese model only and indicated accuracies of 89–97%, ROC values of 0.73–0.75, and Kappa values of 0.06–0.30. The predictive performance of both the DO and Mn models was reasonable, considering all three of these fit metrics and the low percentages of low-DO and high-Mn events in the data.

California↗

USGS2016

Potential utility of environmental DNA for early detection of Eurasian watermilfoil ( Myriophyllum spicatum )

Considering the harmful and irreversible consequences of many biological invasions, early detection of an invasive species is an important step toward protecting ecosystems (Sepulveda et al. 2012). Early detection increases the probability that suppression or eradication efforts will be successful because invasive populations are small and localized (Vander Zanden et al. 2010). However, most invasive species are not detected early because current tools have low detection probabilities when target species are rare and the sampling effort required to achieve acceptable detection capabilities with current tools is seldom tractable (Jerde et al. 2011). As a result, many invasive species go undetected until they are abundant and suppression efforts become costly. Novel DNA-based surveillance tools have recently revolutionized early detection abilities using environmental DNA (eDNA) present in the water (Darling and Mahon 2011, Bohmann et al. 2014). In brief, eDNA monitoring enables the identification of organisms from DNA present and collected in water samples. Aquatic and semiaquatic organisms release DNA contained in sloughed, damaged, or partially decomposed tissue and waste products into the water and molecular techniques allow this eDNA in the water column to be identified from simple and easy-tocollect water samples (Darling and Mahon 2011). Despite limited understanding of the production, persistence, and spread of DNA in water (Barnes et al. 2014), eDNA monitoring has been applied not only to invasive species (Jerde et al. 2011), but also to species that are rare, endangered, or highly elusive (Spear et al. 2014). However, most eDNA research and monitoring has focused on detection of invertebrates and vertebrates and less attentionhas been given to developing eDNA techniques for detecting aquatic invasive plants. Eurasian watermilfoil (EWM; Myriophyllum spicatum L.) is an invasive species for which improved early detection would be particularly helpful. Advanced EWM invasions have negative impacts on native biodiversity, recreational boating, fishing, and other types of aquatic tourism (e.g., Eiswerth et al. 2000). On a broader scale, EWM can also be harmful to man-made aquatic infrastructure, such as hydroelectric dams. If an EWM invasion can be detected in an early stage where eradication is still a possibility, many of these negative consequences can be limited or prevented altogether (e.g., Madsen et al. 2002). The purpose of this research was to develop and validate a traditional polymerase chain reaction (PCR) assay for the detection of pure and hybridized EWM DNA using both laboratory and field experiments. We performed a pilot experiment in outdoor tanks to determine the basic functionality and sensitivity of the assay. Following this initial test, we collected field samples from Michigan and Montana lakes with and without known EWM populations. Taken together, our findings suggest that eDNA techniques have potential to be a useful strategy for the early detection of EWM.

Journal of Aquatic Plant Management↗

USGS2009

Forecasting the combined effects of urbanization and climate change on stream ecosystems: from impacts to management options

Streams collect runoff, heat, and sediment from their watersheds, making them highly vulnerable to anthropogenic disturbances such as urbanization and climate change. Forecasting the effects of these disturbances using process-based models is critical to identifying the form and magnitude of likely impacts. Here, we integrate a new biotic model with four previously developed physical models (downscaled climate projections, stream hydrology, geomorphology, and water temperature) to predict how stream fish growth and reproduction will most probably respond to shifts in climate and urbanization over the next several decades. The biotic submodel couples dynamics in fish populations and habitat suitability to predict fish assemblage composition, based on readily available biotic information (preferences for habitat, temperature, and food, and characteristics of spawning) and day-to-day variability in stream conditions. We illustrate the model using Piedmont headwater streams in the Chesapeake Bay watershed of the USA, projecting ten scenarios: Baseline (low urbanization; no on-going construction; and present-day climate); one Urbanization scenario (higher impervious surface, lower forest cover, significant construction activity); four future climate change scenarios [Hadley CM3 and Parallel Climate Models under medium-high (A2) and medium-low (B2) emissions scenarios]; and the same four climate change scenarios plus Urbanization. Urbanization alone depressed growth or reproduction of 8 of 39 species, while climate change alone depressed 22 to 29 species. Almost every recreationally important species (i.e. trouts, basses, sunfishes) and six of the ten currently most common species were predicted to be significantly stressed. The combined effect of climate change and urbanization on adult growth was sometimes large compared to the effect of either stressor alone. Thus, the model predicts considerable change in fish assemblage composition, including loss of diversity. Synthesis and applications . The interaction of climate change and urban growth may entail significant reconfiguring of headwater streams, including a loss of ecosystem structure and services, which will be more costly than climate change alone. On local scales, stakeholders cannot control climate drivers but they can mitigate stream impacts via careful land use. Therefore, to conserve stream ecosystems, we recommend that proactive measures be taken to insure against species loss or severe population declines. Delays will inevitably exacerbate the impacts of both climate change and urbanization on headwater systems.

Journal of Applied Ecology↗

USGS2025

Demographic mechanisms of snowshoe hare population cycles in Yukon, Canada

One hundred years have elapsed since Charles Elton (1924) described the periodic fluctuations in North American snowshoe hare abundance, yet mechanisms underlying 9–11-year population cycles in snowshoe hares continue to be debated. We applied multistate capture–mark–recapture models to long-term field data (1977–2020) based on >20,000 captures of >7000 unique snowshoe hares ( Lepus americanus ) from Kluane Lake, Yukon, Canada, to estimate and model state-specific demographic parameters. Juveniles had the lowest and reproductive adult females the highest apparent survival. Apparent survival of all sex-age classes was highest during the mid- and late-breeding seasons and was generally better during the increase phase. Conditional probability of females transitioning from non-reproductive to reproductive state, and reproductive females remaining in the reproductive state, increased substantially as the population transitioned from low to increase phase throughout the breeding season. Analysis of stage-structured matrix population models revealed that population-dynamic characteristics were strongly phase-specific, and also varied across seasons, with the increase phases being characterized by high monthly asymptotic population growth rate. Snowshoe hares experienced short stage-specific generation time during the early breeding season across all phases; they experienced relatively long generation time during the increase and low phase of the mid-breeding season, and the increase and peak phase of the late breeding season. Elasticity analyses showed that asymptotic population growth rate was proportionately most sensitive to changes in survival of adult females across all phases and seasons. However, retrospective life table response experiment analysis showed that rapid growth of the snowshoe hare populations during the increase phase was due to improvements in reproductive transitions and pre-weaning survival, whereas population declines are caused primarily by reduced survival (primarily, pre-weaning survival), with reduced reproductive transitions and smaller litter sizes playing a secondary role. Our results suggest that cyclic populations of snowshoe hares are characterized by complex demographic and population-dynamic patterns, depending on phase of the cycle and reproductive season, and that different demographic mechanisms underlie rapid population growth during the increase phase, and swift population declines as the population transitions from the peak to the decline phase. Because our study represents the first comprehensive demographic and population-dynamic study of a cyclic population, similar studies would be needed to test the generalities of our conclusions. Whereas density-dependent predation has been shown to be the primary cause of phase-related changes in survival, future research should focus on identifying mechanisms underlying phase-related changes in reproductive parameters.

Yukon↗

USGS2015

SHRIMP U–Pb and REE data pertaining to the origins of xenotime in Belt Supergroup rocks: evidence for ages of deposition, hydrothermal alteration, and metamorphism

The Belt–Purcell Supergroup, northern Idaho, western Montana, and southern British Columbia, is a thick succession of Mesoproterozoic sedimentary rocks with an age range of about 1470–1400 Ma. Stratigraphic layers within several sedimentary units were sampled to apply the new technique of U–Pb dating of xenotime that sometimes forms as rims on detrital zircon during burial diagenesis; xenotime also can form epitaxial overgrowths on zircon during hydrothermal and metamorphic events. Belt Supergroup units sampled are the Prichard and Revett Formations in the lower Belt, and the McNamara and Garnet Range Formations and Pilcher Quartzite in the upper Belt. Additionally, all samples that yielded xenotime were also processed for detrital zircon to provide maximum age constraints for the time of deposition and information about provenances; the sample of Prichard Formation yielded monazite that was also analyzed. Ten xenotime overgrowths from the Prichard Formation yielded a U–Pb age of 1458 ± 4 Ma. However, because scanning electron microscope – backscattered electrons (SEM–BSE) imagery suggests complications due to possible analysis of multiple age zones, we prefer a slightly older age of 1462 ± 6 Ma derived from the three oldest samples, within error of a previous U–Pb zircon age on the syn-sedimentary Plains sill. We interpret the Prichard xenotime as diagenetic in origin. Monazite from the Prichard Formation, originally thought to be detrital, yielded Cretaceous metamorphic ages. Xenotime from the McNamara and Garnet Range Formations and Pilcher Quartzite formed at about 1160– 1050 Ma, several hundred million years after deposition, and probably also experienced Early Cretaceous growth. These xenotime overgrowths are interpreted as metamorphic–diagenetic in origin (i.e., derived during greenschist facies metamorphism elsewhere in the basin, but deposited in sub-greenschist facies rocks). Several xenotime grains are older detrital grains of igneous derivation. A previous study on the Revett Formation at the Spar Lake Ag–Cu deposit provides data for xenotime overgrowths in several ore zones formed by hydrothermal processes; herein, those results are compared with data from newly analyzed diagenetic, metamorphic, and magmatic xenotime overgrowths. The origin of a xenotime overgrowth is reflected in its rareearth element (REE) pattern. Detrital (i.e., igneous) xenotime has a large negative Eu anomaly and is heavy rare-earth element (HREE)-enriched (similar to REE in igneous zircon). Diagenetic xenotime has a small negative Eu anomaly and flat HREE (Tb to Lu). Hydrothermal xenotime is depleted in light rare-earth element (LREE), has a small negative Eu anomaly, and decreasing HREE. Metamorphic xenotime is very LREE-depleted, has a very small negative Eu anomaly, and is strongly depleted in HREE (from Gd to Lu). Because these characteristics seem to be process related, they may be useful for interpretation of xenotime of unknown origin. The occurrence of 1.16–1.05 Ga metamorphic xenotime, in the apparent absence of pervasive deformation structures, suggests that the heating may be related to poorly understood regional heating due to broad regional underplating of mafic magma. These results may be additional evidence (together with published ages from metamorphic titanite, zircon, monazite, and garnet) for an enigmatic, Grenville-age metamorphic event that is more widely recognized in the southwestern and eastern United States

Alberta, British Columbia, Idaho, Montana, Oregon,↗