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USGS2010

Quantifying restoration success and recovery in a metal-polluted stream: A 17-year assessment of physicochemical and biological responses

Evaluating the effectiveness of stream restoration is often challenging because of the lack of pre-treatment data, narrow focus on physicochemical measures and insufficient post-restoration monitoring. Even when these fundamental elements are present, quantifying restoration success is difficult because of the challenges associated with distinguishing treatment effects from seasonal variation, episodic events and long-term climatic changes.2. We report results of one of the most comprehensive and continuous records of physical, chemical and biological data available to assess restoration success for a stream ecosystem in North America. Over a 17 year period we measured seasonal and annual changes in metal concentrations, physicochemical characteristics, macroinvertebrate communities, and brown trout Salmo trutta populations in the Arkansas River, a metal-contaminated stream in Colorado, USA.3. Although we observed significant improvements in water quality after treatment, the effectiveness of restoration varied temporally, spatially and among biological response variables. The fastest recovery was observed at stations where restoration eliminated point sources of metal contamination. Recovery of macroinvertebrates was significantly delayed at some stations because of residual sediment contamination and because extreme seasonal and episodic variation in metal concentrations prevented recolonization by sensitive species. Synthesis and applications. Because recovery trajectories after the removal of a stressor are often complex or nonlinear, long-term studies are necessary to assess restoration success within the context of episodic events and changes in regional climate. The observed variation in recovery among chemical and biological endpoints highlights the importance of developing objective criteria to assess restoration success. Although the rapid response of macroinvertebrates to reduced metal concentrations is encouraging, we have previously demonstrated that benthic communities from the Arkansas River remained susceptible to other novel anthropogenic stressors. We suggest that the resistance or resilience of benthic macroinvertebrate communities to novel stressors may be effective indicators of restoration success that can account for the non-additive (e.g. synergistic) nature of compound perturbations. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

Journal of Applied Ecology↗

USGS2005

Migratory bird pathways and the Gulf of Mexico: Importance of Louisiana's coast

Because of its geographic position, Louisiana plays an important role in the hemispheric-scale phenomenon known as the Nearctic-Neotropical bird migration system. Each year millions of landbirds migrate across or near to the coast of the Gulf of Mexico. Birds migrate in large, broad fronts that sometimes exceed 2 million individuals, and there is an advantage for them to take a direct north-south route (the shortest distance). During migration seasons, nearly all of the migratory landbird species of the eastern United States, as well as many western species, use the coastal plains of the western gulf. Spring migrants arrive with depleted energy reserves and depend on Louisiana's coastal habitats to provide food and cover after long gulf crossings. Fall migrants depend on Louisiana’s coastal habitats for food to store fat reserves just prior to gulf crossings in autumn. Mortality during the migratory period can be high. Recent research on the black-throated blue warbler ( Dendroica caerulescens ) indicates that more than 85% of the annual mortality for the species occurs during migration. Migrants en route tend to concentrate in habitats adjacent to ecological barriers; DOI land managers need to identify key coastal landscape features that are important to these birds. Because of the vastness of the North American continent, it is nearly impossible to delineate movement patterns and migration pathways by using traditional ground-based surveys.

Fact Sheet↗

USGS2012

White-nose syndrome in bats: U.S. Geological Survey updates

White-nose syndrome (WNS) is a devastating disease that has killed millions of hibernating bats since it first appeared in New York in 2007 and has spread at an alarming rate from the northeastern to the central United States and Canada. The disease is named for the white fungus Geomyces destructans that infects the skin of the muzzle, ears, and wings of hibernating bats. The U.S. Geological Survey (USGS) National Wildlife Health Center (NWHC), the USGS Fort Collins Science Center, the U.S. Fish and Wildlife Service, and other partners continue to play a primary role in WNS research. Studies conducted at the NWHC led to the discovery (Blehert and others, 2009), characterization, and naming (Gargas and others, 2009) of the cold-loving fungus G. destructans and to the development of standardized criteria for diagnosing the disease (Meteyer and others, 2009). Additionally, scientists at the NWHC have pioneered laboratory techniques for studying the effects of the fungus on hibernating bats (Lorch and others, 2011). To determine if bats are affected by white-nose syndrome, scientists look for a characteristic microscopic pattern of skin erosion caused by G. destructans (Meteyer and others, 2009). Field signs of WNS can include visible white fungal growth on the bat's muzzle, wings, or both, but these signs alone are not a reliable disease indicator - laboratory examination and testing are required for disease confirmation. Infected bats also arouse from hibernation more frequently than uninfected bats (Warnecke and others, 2012) and often display abnormal behaviors in their hibernation sites, such as congregating at or near cave openings and daytime flights during winter. These abnormal behaviors may contribute to the bat's accelerated consumption of stored fat reserves, causing emaciation, a characteristic documented in some of the bats that die with WNS. During hibernation, bats likely have lowered immunity (Bouma and others, 2010), which may facilitate the ability of G. destructans to colonize and damage large areas of wing membrane (fig. 2). A current hypothesis suggests that erosion or ulceration of wing membrane caused by the fungus has the potential to alter the physiology of hibernating bats, resulting in fatal disruption of hydration, electrolyte balance, circulation, and thermoregulation (Cryan and others, 2010). Current estimates of bat population declines in the northeastern United States since the emergence of WNS are over 80 percent (Turner and others, 2011). This sudden and widespread mortality associated with WNS is unprecedented in hibernating bats, among which large-scale disease outbreaks have not been previously documented. It is unlikely that species of bats affected by WNS will recover quickly because most are long-lived and have only a single pup per year. Consequently, repopulation after widespread mortality of breeding adults will be a slow process. Worldwide, bats play essential roles as pollinators, seed dispersers, and as primary consumers of insects. The true ecological consequences of the recent large-scale reductions in populations of hibernating bats are not yet known. However, farmers might feel the impact. A recent economic analysis indicated that insect control services (ecosystem services) provided by bats to U.S. agriculture is valued between 4 to 50 billion dollars nationwide per year (Boyles and others, 2011). The number of North American bats estimated to have died from WNS thus far had the capacity to consume up to 8,000 tons of insects per year (Boyles and others, 2011). The area of North America affected by WNS continues to expand. Within the last 2 years, the disease has been confirmed in several Central States, including Alabama, Indiana, Kentucky, Ohio, Tennessee, and Missouri. High mortality of bats has not yet been reported at these locations, and it remains to be seen if WNS will develop and manifest in other States with the same severity as that in the Northeast.

Alabama;Connecticut;Delaware;Illinois;Indiana;Iowa↗

USGS1959

Part 4. Submarine topography and shoal-water ecology

The topography of the sea floor within 10 miles of Saipan broadly resembles that of the land. Eastward, toward the Mariana trench, slopes are about 6°, without prominent benches or scarps. This is inferred to indicate easterly continuation of generally pyroclastic bedrock. The westward slope averages 2° to 3° and consists mainly of nearly flat benches and westfacing scarps. This is taken to imply westward continuation of a limestone bench-and-fault-scarp topography. Projection of known faults to sea and through Tinian, on the basis of topographic trends, suggests a pattern of west-dipping normal faults that parallel the strike of the Mariana ridge and affect the shape and position of islands at the crest of the ridge.

Professional Paper↗

USGS2016

Flexible characterization of animal movement pattern using net squared displacement and a latent state model

Background Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises ( Chelonoidis sp.) using a multi-year (2009–2014) GPS dataset from three different Galapagos Islands. Results With respect to patterns of time spent and the number of transitions between modes, our approach out-performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as “exploratory residence”. Conclusions Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.

Movement Ecology↗

USGS2017

Environmental Escherichia coli : Ecology and public health implications - A review

Escherichia coli is classified as a rod-shaped, Gram-negative bacterium in the family Enterobacteriaceae . The bacterium mainly inhabits the lower intestinal tract of warm-blooded animals, including humans, and is often discharged into the environment through feces or wastewater effluent. The presence of E. coli in environmental waters has long been considered as an indicator of recent fecal pollution. However, numerous recent studies have reported that some specific strains of E. coli can survive for long periods of time, and potentially reproduce, in extra-intestinal environments. This indicates that E. coli can be integrated into indigenous microbial communities in the environment. This naturalization phenomenon calls into question the reliability of E. coli as a fecal indicator bacterium (FIB). Recently, many studies reported that E. coli populations in the environment are affected by ambient environmental conditions affecting their long-term survival. Large-scale studies of population genetics provide the diversity and complexity of E. coli strains in various environments, affected by multiple environmental factors. This review examines the current knowledge on the ecology of E. coli strains in various environments in regards to its role as a FIB and as a naturalized member of indigenous microbial communities. Special emphasis is given on the growth of pathogenic E. coli in the environment, and the population genetics of environmental members of the genus Escherichia . The impact of environmental E. coli on water quality and public health is also discussed.

Journal of Applied Microbiology↗

USGS2007

Seabird behavior as an indicator of food supplies: Sensitivity across the breeding season

We used empirical data on the time allocation of common murres Uria aalge in relation to measures of local prey density to examine whether adults provisioning chicks are more sensitive to changes in prey density than birds that are incubating eggs. We hypothesized that seasonal differences in food requirements of incubating and chick-rearing parents would affect the form of the relationship between time spent at the colony and local food density. We found that the relationship did differ between the incubation and chick-rearing period in 3 important ways: (1) there was a strong non-linear relationship between food density and colony attendance during chick-rearing and a weaker relationship during incubation; (2) incubating birds were able to maintain relatively constant rates of attendance over a wider range of food densities than chick-rearing birds and only reduced colony attendance under extremely poor feeding conditions, if at all; and (3) incubating birds spent more time attending nest sites at the colony than provisioning birds. These differences confirmed that chick-rearing parents are more sensitive to changes in food density than incubating parents, and that measurements of time allocation during the incubation period would have limited value as an indicator of ecosystem change. ?? Inter-Research 2007.

Marine Ecology Progress Series↗

USGS2013

Sexual dimorphism and feeding ecology of Diamond-backed Terrapins ( Malaclemys terrapin )

Natural and sexual selection are frequently invoked as causes of sexual size dimorphism in animals. Many species of turtles, including the Diamond-backed Terrapin (Malaclemys terrapin), exhibit sexual dimorphism in body size, possibly enabling the sexes to exploit different resources and reduce intraspecific competition. Female terrapins not only have larger body sizes but also disproportionately larger skulls and jaws relative to males. To better understand the relationship between skull morphology and terrapin feeding ecology, we measured the in-lever to out-lever ratios of 27 male and 33 female terrapin jaws to evaluate biomechanics of the trophic apparatus. In addition, we measured prey handling times by feeding Fiddler Crabs (Uca pugnax), a natural prey item, to 24 terrapins in the laboratory. Our results indicate that although females have disproportionately larger heads, they have similar in:out lever ratios to males, suggesting that differences in adductor muscle mass are more important in determining bite force than jaw in:out lever ratios. Females also had considerably reduced prey handling times. Understanding the factors affecting terrapin feeding ecology can illuminate the potential roles male and female terrapins play as top-down predators that regulate grazing of Periwinkle Snails (Littorina irrorata) on Cord Grass (Spartina alterniflora).

Herpetologica↗

USGS2019

The area under the precision‐recall curve as a performance metric for rare binary events

Species distribution models are used to study biogeographic patterns and guide decision‐making. The variable quality of these models makes it critical to assess whether a model's outputs are suitable for the intended use, but commonly used evaluation approaches are inappropriate for many ecological contexts. In particular, unrealistically high performance assessments have been associated with models for rare species and predictions over large geographic extents. We evaluated the area under the precision‐recall curve (AUC‐PR) as a performance metric for rare binary events, focusing on the assessment of species distribution models. Precision is the probability that a species is present given a predicted presence, while recall (more commonly called sensitivity) is the probability the model predicts presence in locations where the species has been observed. We simulated species at three levels of prevalence, compared AUC‐PR and the area under the receiver operating characteristic curve (AUC‐ROC) when the geographic extent of predictions was increased and assessed how well each metric reflected a model's utility to guide surveys for new populations. AUC‐PR was robust to species rarity and, unlike AUC‐ROC, not affected by an increasing geographic extent. The major advantages of AUC‐PR arise because it does not incorporate correctly predicted absences and is therefore less prone to exaggerate model performance for unbalanced datasets. AUC‐PR and precision were useful indicators of a model's utility for guiding surveys. We show that AUC‐PR has important advantages for evaluating models of rare species, and its benefits in the context of unbalanced binary responses will make it applicable for other ecological studies. By not considering the true negative quadrant of the confusion matrix, AUC‐PR ameliorates issues that arise when the geographic extent is increased beyond the species’ range or when a large number of background points are used when absence information is unavailable. However, no single metric captures all aspects of performance nor provides an absolute index that can be compared across datasets. Our results indicate AUC‐PR and precision can provide useful and intuitive metrics for evaluating a model's utility for guiding sampling, and can complement other metrics to help delineate a model's appropriate use.

Methods in Ecology and Evolution↗

USGS2010

Predicting performance for ecological restoration: A case study using Spartina altemiflora

The success of population-based ecological restoration relies on the growth and reproductive performance of selected donor materials, whether consisting of whole plants or seed. Accurately predicting performance requires an understanding of a variety of underlying processes, particularly gene flow and selection, which can be measured, at least in part, using surrogates such as neutral marker genetic distances and simple latitudinal effects. Here we apply a structural equation modeling approach to understanding and predicting performance in a widespread salt marsh grass, Spartina alterniflora, commonly used for ecological restoration throughout its native range in North America. We collected source materials from throughout this range, consisting of eight clones each from 23 populations, for transplantation to a common garden site in coastal Louisiana and monitored their performance. We modeled performance as a latent process described by multiple indicator variables (e.g., clone diameter, stem number) and estimated direct and indirect influences of geographic and genetic distances on performance. Genetic distances were determined by comparison of neutral molecular markers with those from a local population at the common garden site. Geographic distance metrics included dispersal distance (the minimum distance over water between donor and experimental sites) and latitude. Model results indicate direct effects of genetic distance and latitude on performance variation among the donor sites. Standardized effect strengths indicate that performance was roughly twice as sensitive to variation in genetic distance as to latitudinal variation. Dispersal distance had an indirect influence on performance through effects on genetic distance, indicating a typical pattern of genetic isolation by distance. Latitude also had an indirect effect on genetic distance through its linear relationship with dispersal distance. Three performance indicators had significant loadings on performance alone (mean clone diameter, mean number of stems, mean number of inflorescences), while the performance indicators mean stem height and mean stem width were also influenced by latitude. We suggest that dispersal distance and latitude should provide an adequate means of predicting performance in future S. alterniflora restorations and propose a maximum sampling distance of 300 km (holding latitude constant) to avoid the sampling of inappropriate ecotypes. ?? 2010 by the Ecological Society of America.

Ecological Applications↗

USGS2021

Determination of burn severity models ranging from regional to continental scales for the conterminous United States

Identifying meaningful measures of ecological change over large areas is dependent on the quantification of robust relationships between ecological metrics and remote sensing products. Over the past several decades, ground observations of wildfire and prescribed fire severity have been acquired across hundreds of wildland fires in the United States, primarily utilizing the Composite Burn Index (CBI) plot protocol. These observations have been coupled to spaceborne passive spectral reflectance indices (e.g. Landsat-derived variations of the Normalized Burn Ratio [NBR]) to produce regression models describing their relationship. Here we develop regression models by vegetation type for multiple vegetation classification systems representing a range of spatial scales, and a decision tree framework for evaluating these regression models. Our overall goals were to determine which scale of ecological classifications provided the best estimate of burn severity from Landsat data and how to choose the best regression model. We aggregated a total of 6280 CBI plots for 234 wildland fires that burned between 1994 and 2017 and produced Landsat-derived NBR and differenced NBR (dNBR) values for each plot. We then calculated best fit linear or higher order regression equations between CBI and NBR/dNBR for each landcover classification system from smallest to largest scale: LANDFIRE Biophysical Settings (BPS), National Vegetation Classification macrogroup (NVC) landcover classifications, Omernick III, II, and I ecoregions, LANDFIRE Fire Regime Groups (FRG), and the entire conterminous United States (CONUS) dataset. The CONUS regression model goodness of fit was moderate (R 2 = 0.55, P < 0.001) for dNBR and poor (R 2 = 0.30, P < 0.001) for NBR. Within landcover classifications, CBI was better fit by dNBR than NBR. Finer scale regional regression models including BPS (dNBR R 2 ¯ "> R2¯ = 0.56 and 0.00–0.83 R 2 range; NBR R 2 ¯ "> R(bar) 2 = 0.43 and 0.00–0.82 R 2 range) and NVC (dNBR R 2 ¯ "> R(bar) 2 = 0.55 and 0.15–0.78 R 2 range; NBR R 2 ¯ "> R(bar) 2 = 0.41 and 0.00–0.79 R 2 range) were on average the same or better than the CONUS models for dNBR and NBR, with the strongest fit models exhibiting R 2 ≥ 0.70, whereas larger scale regional models R 2 ¯ "> R(bar) 2 ranged from 0.28 to 0.5. However, variation in accuracy among landcover types indicate that dNBR and NBR regression models could be used to effectively estimate CBI for future fires in certain regions, while for other regions models may require additional field observations or alternative spectral transformations. Our decision tree schema can be used to help users determine which scale is likely to produce the most accurate results using our models. The CBI regression models developed here, paired with the decision tree, provide users with a simple method to estimate burn severity in units of CBI for any fire within CONUS with moderate to high levels of confidence and provide a template for further development of models with new data going forward.

Conterminous United States↗

USGS2023

Reconstructing missing data by comparing interpolation techniques: Applications for long-term water quality data

Missing data are typical yet must be addressed for proper inferences or expanding datasets to guide our limnological understanding and management of aquatic systems. Interpolation methods (i.e., estimating missing values using known values within the dataset) can alleviate data gaps and common problems. We compared seven popular interpolation methods for predicting substantial missingness in a long-term water quality dataset from the Upper Mississippi River, U.S.A. The dataset included 80,000 sampling sites collected over 30 yr that had substantial missingness for total nitrogen (TN), total phosphorus (TP), and water velocity. For all three interpolated water quality variables, random forests had very high prediction accuracy and outperformed the methods of ordinary kriging, polynomial regressions, regression trees, and inverse distance weighting. TP had a mean absolute error (MAE) of 0.03 mg (L-TP) −1 , TN had a MAE of 0.39 mg (L-TN) −1 , and water velocity had a MAE of 0.10 m s −1 . The random forests' error rates were mapped and showed low spatiotemporal variability across the riverscape, indicating high model performance across many habitat types and large spatial scales. In the current era of “big data,” interpolation becomes an imperative step prior to ecological analyses yet remains unfamiliar and underutilized. Our research briefly describes the importance of addressing missingness and provides a roadmap to conduct model intercomparisons of other big datasets. We also share adaptable data analysis scripts, which allows others to readily conduct interpolation comparisons for many limnology applications and contexts.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗

USGS2008

Mapping the information landscape: Discerning peaks and valleys for ecological monitoring

We investigate previously unreported phenomena that have a potentially significant impact on the design of surveillance monitoring programs for ecological systems. Ecological monitoring practitioners have long recognized that different species are differentially informative of a system's dynamics, as codified in the well-known concepts of indicator or keystone species. Using a novel combination of analysis techniques from nonlinear dynamics, we describe marked variation among spatial sites in information content with respect to system dynamics in the entire region. We first observed these phenomena in a spatially extended predator-prey model, but we observed strikingly similar features in verified water-level data from a NOAA/NOS Great Lakes monitoring program. We suggest that these features may be widespread and the design of surveillance monitoring programs should reflect knowledge of their existence.

Journal of Biological Physics↗

USGS2013

Diatom evidence for the onset of Pliocene cooling from AND-1B, McMurdo Sound, Antarctica

The late Pliocene, ~ 3.3–3.0 Ma, is the most recent interval of sustained global warmth in the geologic past. This window is the focus of climate reconstruction efforts by the U.S. Geological Survey's Pliocene Research, Interpretation, and Synoptic Mapping (PRISM) Data/Model Cooperative, and may provide a useful climate analog for the coming century. Reconstructions of past surface ocean conditions proximal to the Antarctic continent are essential to understanding the sensitivity of the cryosphere to this key interval in Earth's climate evolution. An exceptional marine sediment core collected from the southwestern Ross Sea (78° S), Antarctica, during ANDRILL's McMurdo Ice Shelf Project preserves evidence of dramatic fluctuations between grounded ice and productive, open ocean conditions during the late Pliocene, reflecting orbitally-paced glacial/interglacial cycling. In this near-shore record, diatom-rich sediments are recovered from interglacial intervals; two of these diatomites, from ~ 3.2 Ma and 3.03 Ma, are within the PRISM chronologic window. The diatom assemblages identified in PRISM-age late Pliocene diatom-rich sediments are distinct from those in mid-Pliocene and later Pliocene/Pleistocene intervals recovered from AND-1B, and comprise both extant taxa with well-constrained ecological preferences and a diverse extinct flora, some members of which are previously undescribed from Antarctic sediments. Both units are dominated by Chaetoceros resting spores, an indicator of high productivity and stratification that is present at much lower abundance in materials both older and younger than the PRISM-age sediments. Newly described species of the genus Fragilariopsis , which first appear in the AND-1B record at 3.2 Ma, are the most abundant extinct members of the PRISM-age assemblages. Other extant species with established environmental affinities, such as Fragilariopsis sublinearis , F . curta , Stellarima microtrias , and Thalassiothrix antarctica , are present at lower abundances. Environmental inferences drawn from extant diatom assemblages are in good agreement with those from Chaetoceros resting spores and the Fragilariopsis radiation. All three lines of evidence indicate the onset of late Pliocene cooling in the Ross Sea near-shore environment at 3.2 Ma, with intensification and possible regional persistence of summer sea ice by 3.03 Ma. An important implication of this research is the indication that the Ross Ice Shelf fluctuated dramatically on orbital timescales at a time when nearshore Antarctic conditions were only modestly warmer than present.

Palaeogeography, Palaeoclimatology, Palaeoecology↗

USGS2020

Spatial distribution of heavy metals in the West Dongting Lake floodplain, China

The protection of Dongting Lake is important because it is an overwintering and migration route for many rare and endangered birds of East Asia and Australasia, but an assessment of heavy metal contamination in West Dongting Lake is lacking. A total of 75 sediment samples (five sites x three sediment depths x five repeats) were collected in West Dongting Lake in January 2017 to assess the spatial distribution and ecological risk of heavy metal in West Dongting Lake. Heavy metal values varied by sediment depth including As, Cd, Zn, and Cu, with depth giving an indication of recent vs. historical deposition. The major input of Hg, Cu, Ni may come from continued anthropogenic activities related to regional industrial activities within Yuan River and Li River whereas, the major sources of spread Cd pollution may be from agricultural fertilizers.

West Dongting Lake floodplain↗

USGS2021

Cloud water interception in Hawai‘i: Developing capacity to characterize the spatial patterns and effects on water and ecological processes responses in Hawai‘i

Cloud-water interception (CWI) is the process by which fog or cloud water droplets are captured and accumulate on the leaves and branches of plants, some of which drips to the ground. Prior studies in Hawai'i indicate that CWI is highly variable and can contribute substantially to total precipitation. In this study, we monitored CWI and other processes at five mountain field sites on the Islands of Oʻahu, Maui, and Hawaiʻi to explore how CWI (1) varies with different climate and vegetation characteristics, (2) affects plant water use and growth, and (3) contributes to water resources. Results show that annual CWI varied from 158 to 910 mm, accounting for 3-34% of total water input at individual sites. This large variation was caused by differences in the quantity of cloud water, wind speed, and vegetation structure between sites. We developed a model to predict CWI using both climatic and forest canopy characteristics. On average, the model underestimated annual CWI by 18%, but reproduced the site differences relatively well. Plant water use decreased during periods of fog events mainly because of associated higher humidity. This new CWI model can be used to assess impacts of climate and land cover change on CWI and provide valuable information for resource management in Hawai‘i, which was not previously possible. At one field site, we explored the impacts of fog water on hydrological and ecological processes. Fog effects on native plant growth were indirect, primarily buffering effects of solar radiation. Removal of grass allowed natural regeneration of seedlings but did not alter soil moisture values. A soil data-collection program was initiated to help evaluate the role CWI has in providing moisture for plants, reducing wildfire risk within the fog zone, and contributing to groundwater recharge to aquifers that supply drinking water and groundwater discharge to streams.

Hawaii↗

USGS2016

Assessing models of speciation under different biogeographic scenarios; An empirical study using multi-locus and RNA-seq analyses

Evolutionary biology often seeks to decipher the drivers of speciation, and much debate persists over the relative importance of isolation and gene flow in the formation of new species. Genetic studies of closely related species can assess if gene flow was present during speciation, because signatures of past introgression often persist in the genome. We test hypotheses on which mechanisms of speciation drove diversity among three distinct lineages of desert tortoise in the genus Gopherus . These lineages offer a powerful system to study speciation, because different biogeographic patterns (physical vs. ecological segregation) are observed at opposing ends of their distributions. We use 82 samples collected from 38 sites, representing the entire species' distribution and generate sequence data for mtDNA and four nuclear loci. A multilocus phylogenetic analysis in *BEAST estimates the species tree. RNA‐seq data yield 20,126 synonymous variants from 7665 contigs from two individuals of each of the three lineages. Analyses of these data using the demographic inference package ∂a∂i serve to test the null hypothesis of no gene flow during divergence. The best‐fit demographic model for the three taxa is concordant with the *BEAST species tree, and the ∂a∂i analysis does not indicate gene flow among any of the three lineages during their divergence. These analyses suggest that divergence among the lineages occurred in the absence of gene flow and in this scenario the genetic signature of ecological isolation (parapatric model) cannot be differentiated from geographic isolation (allopatric model).

Ecology and Evolution↗

USGS2013

Worldwide phylogenetic relationship of avian poxviruses

Poxvirus infections have been found in 230 species of wild and domestic birds worldwide in both terrestrial and marine environments. This ubiquity raises the question of how infection has been transmitted and globally dispersed. We present a comprehensive global phylogeny of 111 novel poxvirus isolates in addition to all available sequences from GenBank. Phylogenetic analysis of the Avipoxvirus genus has traditionally relied on one gene region (4b core protein). In this study we expanded the analyses to include a second locus (DNA polymerase gene), allowing for a more robust phylogenetic framework, finer genetic resolution within specific groups, and the detection of potential recombination. Our phylogenetic results reveal several major features of avipoxvirus evolution and ecology and propose an updated avipoxvirus taxonomy, including three novel subclades. The characterization of poxviruses from 57 species of birds in this study extends the current knowledge of their host range and provides the first evidence of the phylogenetic effect of genetic recombination of avipoxviruses. The repeated occurrence of avian family or order-specific grouping within certain clades (e.g., starling poxvirus, falcon poxvirus, raptor poxvirus, etc.) indicates a marked role of host adaptation, while the sharing of poxvirus species within prey-predator systems emphasizes the capacity for cross-species infection and limited host adaptation. Our study provides a broad and comprehensive phylogenetic analysis of the Avipoxvirus genus, an ecologically and environmentally important viral group, to formulate a genome sequencing strategy that will clarify avipoxvirus taxonomy.

Journal of Virology↗