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Brian S. Cade

Publications and source records attributed to Brian S. Cade.

At least 19 recordsLinked to original sources
USGS2025

Growth rate variation in Brown Treesnakes (Boiga irregularis): An invasive species of conservation concern

Somatic growth rate is a fundamental trait that influences metabolism, lifespan and reproductive maturity and is critical for understanding population dynamics and informing management actions. Brown Treesnakes ( Boiga irregularis ) introduced to Guam are highly invasive and can reproduce year-round without discrete cohorts. We compared snake size trajectories described by the conventionally used von Bertalanffy growth function versus the Gompertz model. Using quantile regression with a regularized effect for individual snakes we modeled growth rates of 270 marked, wild snakes as a function of size. The Gompertz model explained more of the variation in growth and rendered more realistic predictions of asymptotic sizes than did the von Bertalanffy model. With the Gompertz model, growth rates were 1.05–1.16× faster in males than in females. Females reached asymptotic sizes at shorter snout-vent lengths than males. Growth rate was positively correlated with amount of precipitation, and modeling wet-dry seasonality on Guam as a sinusoidal function identified a growth peak in September—October. Effects of seasonality and precipitation, however, were minor compared to individual and sex related differences in size-adjusted growth rates. We estimated that the 50th (and 5th, 95th) growth-rate percentile males in our study population become sexually mature at an age of 33 (∞, 15) months, while females mature at 41 (∞, 18) months, where ∞ indicates that the slowest growing snakes never reach maturity. However, 50% of the snakes mature at a size below the median, and age at maturity may be as low as 10.4 (males) and 13.7 (females) months for average-sized hatchlings that grow fast. Our results have implications for the timing of management options for this species and our approach can be broadly applied to animals where repeated growth data are obtained and age is unknown.

Ecology and Evolution↗
USGS2022

Potential cheatgrass abundance within lightly invaded areas of the Great Basin

Context Anticipating where an invasive species could become abundant can help guide prevention and control efforts aimed at reducing invasion impacts. Information on potential abundance can be combined with information on the current status of an invasion to guide management towards currently uninvaded locations where the threat of invasion is high. Objectives We aimed to support management by developing predictive maps of potential cover for cheatgrass ( Bromus tectorum ), a problematic invader that can transform plant communities. We integrated our predictions of potential abundance with mapped estimates of current cover to quantify invasion potential within lightly invaded areas. Methods We used quantile regression to model cheatgrass abundance as a function of climate, weather, and disturbance, treating outputs as low to high invasion scenarios. We developed a species-specific set of covariates and validated model performance using spatially and temporally independent data. Results Potential cheatgrass abundance was higher in areas that had burned, at low elevations, and when fall germination conditions were more favorable. Our results highlight the extensive areas across the Great Basin where cheatgrass abundance could increase to levels that can alter fire behavior and cause other ecological impacts. Conclusions We predict potential cheatgrass abundance to quantify relative invasion risk. Our model results provide high and low scenarios of cheatgrass abundance to guide resource allocation and planning efforts across shrubland ecosystems of the Great Basin that remain relatively uninvaded. Combining information on an invasive species’ current and potential abundance can yield spatial predictions to guide resource allocation and management action.

California, Idaho, Nevada, Oregon, Utah↗
USGS2022

Assessing vegetation recovery from energy development using a dynamic reference approach

Ecologically relevant references are useful for evaluating ecosystem recovery, but references that are temporally static may be less useful when environmental conditions and disturbances are spatially and temporally heterogeneous. This challenge is particularly acute for ecosystems dominated by sagebrush ( Artemisia spp.), where communities may require decades to recover from disturbance. We demonstrated application of a dynamic reference approach to studying sagebrush recovery using three decades of sagebrush cover estimates from remote sensing (1985–2018). We modelled recovery on former oil and gas well pads ( n = 1200) across southwestern Wyoming, USA, relative to paired references identified by the Disturbance Automated Reference Toolset. We also used quantile regression to account for unmodelled heterogeneity in recovery, and projected recovery from similar disturbance across the landscape. Responses to weather and site-level factors often differed among quantiles, and sagebrush recovery on former well pads increased more when paired reference sites had greater sagebrush cover. Little (<5%) of the landscape was projected to recover within 100 years for low to mid quantiles, and recovery often occurred at higher elevations with cool and moist annual conditions. Conversely, 48%–78% of the landscape recovered quickly (within 25 years) for high quantiles of sagebrush cover. Our study demonstrates advantages of using dynamic reference sites when studying vegetation recovery, as well as how additional inferences obtained from quantile regression can inform management.

Wyoming↗
USGS2021

Thermal stability of an adaptable, invasive ectotherm: Argentine giant tegus in the Greater Everglades ecosystem, USA

Invasive species globally threaten biodiversity and economies, but the ecophysiological mechanisms underlying their success are often understudied. For those alien species that also exhibit high phenotypic plasticity, such as habitat generalists, adaptations in response to environmental pressures can take place relatively quickly. The Argentine giant tegu ( Salvator merianae ; tegu) is a large omnivorous lizard from South America that is prolific, long-lived, vagile, and highly adaptable to disturbed environments. They are well suited to the climate of southeastern United States, introduced to several disjunct areas, including the Everglades, where their voracious appetite threatens native wildlife. Tegus undergo winter dormancy (hibernation) to cope with colder temperatures, and while this behavior may facilitate invasion into more temperate regions, it may also present management opportunities. We studied the thermal habits of wild S. merianae within their invaded range in southern Florida, USA. We used radiotelemetry and trail cameras to verify aboveground behaviors, and temperature dataloggers to monitor surface (sun-exposed [ T e ] and shaded [ T s ]), ambient ( T a ), subsurface ground ( T h ), and internal body ( T b ) temperatures of a population of free-ranging tegus over several seasons. We evaluated thermal and behavioral data and identified five biologically significant periods: pre-hibernal, hibernal, cold snaps, hibernal-basking, and post-hibernal. We found tegus maintained thermal stability throughout the hibernal period, frequently at temperatures above available thermal microhabitats. Variation in T b was lowest during hibernation and cold snaps and was less variable than subsurface temperatures despite not leaving their hibernaculum. Hibernal ingress and egress were best predicted by temperature differentials between exposed soil and ambient daily mean temperatures ( T e − T a ) and daylength. Though we detected no sex differences, larger animals started hibernation sooner, stayed in hibernation longer, and retained higher fat stores over the study period. One individual did not hibernate, representing only the second record of this behavior. Despite limitations of these descriptive data, this is the first study finely detailing T b of a population of wild, free-ranging S. merianae over multiple biologically significant time periods and to associate T b with thermal habitats within its invasive range. Tegus' apparent ability for thermal stability expands the adaptability breadth of this species and underscores the invasion threat.

Florida↗
USGS2020

Latitudinal patterns of alien plant invasions

Latitudinal patterns of biodiversity have long been a central topic in ecology and evolutionary biology. However, while most previous studies have focused on native species, little effort has been devoted to latitudinal patterns of plant invasions (with a few exceptions based on data from sparse locations). Using the most up‐to‐date worldwide native and alien plant distribution data from 801 regions (including islands), we compared invasion levels (i.e. alien richness/total richness) in the Northern and Southern Hemispheres and across continental regions and islands around the globe. Results from quantile regressions using B‐splines to model nonlinearity showed (1) declining richness with increasing latitude, although the highest alien richness occurs at around 40 degrees in both hemispheres, (2) decreasing invasion levels towards higher latitudes on islands but a unimodal pattern in invasion level in continental regions in each hemisphere, (3) significantly higher invasion levels on islands than in continental regions and (4) a greater variability in invasion levels on islands at low latitudes than on high‐latitude islands. In continental regions, only the mid‐latitudes had high variability with both low and high invasion levels. Our findings identified latitudes with invasion hotspots where management is urgently needed, and latitudes with many areas of low invasions but high conservation potential where prevention of future invasions should be the priority.

Journal of Biogeography↗
USGS2020

Comment on “Female toads engaging in adaptive hybridization prefer high-quality heterospecifics as mates”

Chen and Pfennig (Reports, 20 March 2020, p. 1377) analyze the fitness consequences of hybridization in toads but do not account for differences in survival among progeny. Apparent fitness effects depend on families with anomalously low survival, yet survival is crucial to evolutionary fitness. This and other analytical shortcomings demonstrate that a conclusion of adaptive mate choice is not yet justified.

Science↗
USGS2019

Diversity and abundance of wild bees in an agriculturally dominated landscape of eastern Colorado

Agricultural intensification has resulted in loss of natural and semi-natural habitats impacting several important ecosystem services. One group of organisms that has suffered greatly are the bees and hence pollination, the supporting ecosystem service they complete. The United States Department of Agriculture (USDA) Conservation Reserve Program (CRP) has implemented conservation practices designed to improve habitat for pollinators in agroecosystems by paying to recover environmentally sensitive agricultural land from production, and restoring them by planting native grass mixes, pollinator-friendly legumes and wildflowers. Our study, aimed at demonstrating the efficacy of this practice, measured diversity and abundance of wild bee genera in the agricultural landscape of eastern semiarid regions of Colorado, USA, where CRP practices were implemented. Over our 3-year study, we obtained a total of 16,207 bees belonging to 51 genera. We found inconsistent differences in number of bee genera and abundance of bees in CRP fields supplemented with wildflowers compared to those with conventional grass seed mix. However, we observed only a 40–80% overlap in bee genera between fields supplemented with wildflowers and those with grass seed mixes indicating that diversity was enhanced by having both habitats. With the caveat that 3 years is a very short period to see appreciable changes, our results suggest that recovering environmentally sensitive land can strengthen pollinator populations in landscapes dominated by agricultural activities. In addition, periodic evaluation and maintenance of these recovered lands will further support the efforts towards revitalization of ecosystem services in these areas.

Colorado↗
USGS2018

Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts

Many different factors influence animal activity. Often, the value of an environmental variable may influence significantly the upper or lower tails of the activity distribution. For describing relationships with heterogeneous boundaries, quantile regressions predict a quantile of the conditional distribution of the dependent variable. A quantile count model extends linear quantile regression methods to discrete response variables, and is useful if activity is quantified by trapping, where there may be many tied (equal) values in the activity distribution, over a small range of discrete values. Additionally, different environmental variables in combination may have synergistic or antagonistic effects on activity, so examining their effects together, in a modeling framework, is a useful approach. Thus, model selection on quantile counts can be used to determine the relative importance of different variables in determining activity, across the entire distribution of capture results. We conducted model selection on quantile count models to describe the factors affecting activity (numbers of captures) of cane toads ( Rhinella marina ) in response to several environmental variables (humidity, temperature, rainfall, wind speed, and moon luminosity) over eleven months of trapping. Environmental effects on activity are understudied in this pest animal. In the dry season, model selection on quantile count models suggested that rainfall positively affected activity, especially near the lower tails of the activity distribution. In the wet season, wind speed limited activity near the maximum of the distribution, while minimum activity increased with minimum temperature. This statistical methodology allowed us to explore, in depth, how environmental factors influenced activity across the entire distribution, and is applicable to any survey or trapping regime, in which environmental variables affect activity.

Ecosphere↗
USGS2017

Efficacy of SpayVac® as a contraceptive in feral horses

ABSTRACT We tested the efficacy of 2 formulations of the immunocontraceptive SpayVac1, which packages the immunogen porcine zona pellucida (PZP) and an adjuvant in multilamellar liposomes, as a contraceptive in captive feral horses (Equus caballus) for 3 consecutive breeding seasons (Pauls Valley, OK, USA; 2012–2014) following a single inoculation. Annual fertility rates in control adult female horses (n ¼ 30 each yr) were 100%, 96.7%, and 100%. In the nonaqueous treatment group, fertility was 16.7% in the first year (n ¼ 30) and 75.9% in the second year (n ¼ 29), at which point we dropped the group from the study. Fertility rates in the aqueous group were 13.3%, 46.7%, and 43.3% (n ¼ 30 each yr). Fifteen of the females in the aqueous group were infertile in all 3 years. Across 11 sampling dates postvaccination, mean PZP antibody titers in serum were 33.7–91.9% greater in nonpregnant females than pregnant females for the aqueous treatment group and 7.8–82.8% greater for the nonaqueous group. However, the 15 consistently infertile females did not necessarily have the greatest antibody titers. Reactions at the injection site occurred in 29.8% of the 84 females that received an injection other than saline solution, but there was no evidence that the reactions were painful or affected mobility. The nonaqueous formulation produced more local reactions than did the aqueous, but presence of PZP did not increase the frequency of reactions above that seen with liposomes þ adjuvant. Uterine edema was not found at frequencies greater than would be expected in untreated females. Additional research to explore relationships between vaccine dose, adjuvant, and efficacy is warranted. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Wildlife Society Bulletin↗
USGS2017

Logistic quantile regression provides improved estimates for bounded avian counts: A case study of California Spotted Owl fledgling production

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical conditional distribution of a bounded discrete random variable. The logistic quantile regression model requires that counts are randomly jittered to a continuous random variable, logit transformed to bound them between specified lower and upper values, then estimated in conventional linear quantile regression, repeating the 3 steps and averaging estimates. Back-transformation to the original discrete scale relies on the fact that quantiles are equivariant to monotonic transformations. We demonstrate this statistical procedure by modeling 20 years of California Spotted Owl fledgling production (0−3 per territory) on the Lassen National Forest, California, USA, as related to climate, demographic, and landscape habitat characteristics at territories. Spotted Owl fledgling counts increased nonlinearly with decreasing precipitation in the early nesting period, in the winter prior to nesting, and in the prior growing season; with increasing minimum temperatures in the early nesting period; with adult compared to subadult parents; when there was no fledgling production in the prior year; and when percentage of the landscape surrounding nesting sites (202 ha) with trees ≥25 m height increased. Changes in production were primarily driven by changes in the proportion of territories with 2 or 3 fledglings. Average variances of the discrete cumulative distributions of the estimated fledgling counts indicated that temporal changes in climate and parent age class explained 18% of the annual variance in owl fledgling production, which was 34% of the total variance. Prior fledgling production explained as much of the variance in the fledgling counts as climate, parent age class, and landscape habitat predictors. Our logistic quantile regression model can be used for any discrete response variables with fixed upper and lower bounds.

The Auk↗
USGS2016

Trophic magnification of organic chemicals: A global synthesis

Production of organic chemicals (OCs) is increasing exponentially, and some OCs biomagnify through food webs to potentially toxic levels. Biomagnification under field conditions is best described by trophic magnification factors (TMFs; per trophic level change in log-concentration of a chemical) which have been measured for more than two decades. Syntheses of TMF behavior relative to chemical traits and ecosystem properties are lacking. We analyzed >1500 TMFs to identify OCs predisposed to biomagnify and to assess ecosystem vulnerability. The highest TMFs were for OCs that are slowly metabolized by animals (metabolic rate k M < 0.01 day &ndash;1 ) and are moderately hydrophobic (log K OW 6&ndash;8). TMFs were more variable in marine than freshwaters, unrelated to latitude, and highest in food webs containing endotherms. We modeled the probability that any OC would biomagnify as a combined function of K OW and k M . Probability is greatest (&sim;100%) for slowly metabolized compounds, regardless of K OW , and lowest for chemicals with rapid transformation rates ( k M > 0.2 day &ndash;1 ). This probabilistic model provides a new global tool for screening existing and new OCs for their biomagnification potential.

Environmental Science & Technology↗
USGS2016

Conditional vulnerability of plant diversity to atmospheric nitrogen deposition across the United States

Atmospheric nitrogen (N) deposition has been shown to decrease plant species richness along regional deposition gradients in Europe and in experimental manipulations. However, the general response of species richness to N deposition across different vegetation types, soil conditions, and climates remains largely unknown even though responses may be contingent on these environmental factors. We assessed the effect of N deposition on herbaceous richness for 15,136 forest, woodland, shrubland, and grassland sites across the continental United States, to address how edaphic and climatic conditions altered vulnerability to this stressor. In our dataset, with N deposition ranging from 1 to 19 kg N&sdot;ha&minus;1&sdot;y&minus;1, we found a unimodal relationship; richness increased at low deposition levels and decreased above 8.7 and 13.4 kg N&sdot;ha&minus;1&sdot;y&minus;1 in open and closed-canopy vegetation, respectively. N deposition exceeded critical loads for loss of plant species richness in 24% of 15,136 sites examined nationwide. There were negative relationships between species richness and N deposition in 36% of 44 community gradients. Vulnerability to N deposition was consistently higher in more acidic soils whereas the moderating roles of temperature and precipitation varied across scales. We demonstrate here that negative relationships between N deposition and species richness are common, albeit not universal, and that fine-scale processes can moderate vegetation responses to N deposition. Our results highlight the importance of contingent factors when estimating ecosystem vulnerability to N deposition and suggest that N deposition is affecting species richness in forested and nonforested systems across much of the continental United States.

PNAS↗
USGS2015

Assessment of surface water chloride and conductivity trends in areas of unconventional oil and gas development — Why existing national data sets cannot tell us what we would like to know

Heightened concern regarding the potential effects of unconventional oil and gas development on regional water quality has emerged, but the few studies on this topic are limited in geographic scope. Here we evaluate the potential utility of national and publicly available water-quality data sets for addressing questions regarding unconventional oil and gas development. We used existing U.S. Geological Survey and U.S. Environmental Protection Agency data sets to increase understanding of the spatial distribution of unconventional oil and gas development in the U.S. and broadly assess surface water quality trends in these areas. Based on sample size limitations, we were able to estimate trends in specific conductance (SC) and chloride (Cl − ) from 1970 to 2010 in 16% ( n = 155) of the watersheds with unconventional oil and gas resources. We assessed these trends relative to spatiotemporal distributions of hydraulically fractured wells. Results from this limited analysis suggest no consistent and widespread trends in surface water quality for SC and Cl − in areas with increasing unconventional oil and gas development and highlight limitations of existing national databases for addressing questions regarding unconventional oil and gas development and water quality.

Water Resources Research↗
USGS2015

Model averaging and muddled multimodel inferences

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial effects for individual predictors when there is multicollinearity among the predictor variables. Multicollinearity implies that the scaling of units in the denominators of the regression coefficients may change across models such that neither the parameters nor their estimates have common scales, therefore averaging them makes no sense. The associated sums of AIC model weights recommended to assess relative importance of individual predictors are really a measure of relative importance of models, with little information about contributions by individual predictors compared to other measures of relative importance based on effects size or variance reduction. Sometimes the model-averaged regression coefficients for predictor variables are incorrectly used to make model-averaged predictions of the response variable when the models are not linear in the parameters. I demonstrate the issues with the first two practices using the college grade point average example extensively analyzed by Burnham and Anderson. I show how partial standard deviations of the predictor variables can be used to detect changing scales of their estimates with multicollinearity. Standardizing estimates based on partial standard deviations for their variables can be used to make the scaling of the estimates commensurate across models, a necessary but not sufficient condition for model averaging of the estimates to be sensible. A unimodal distribution of estimates and valid interpretation of individual parameters are additional requisite conditions. The standardized estimates or equivalently the t statistics on unstandardized estimates also can be used to provide more informative measures of relative importance than sums of AIC weights. Finally, I illustrate how seriously compromised statistical interpretations and predictions can be for all three of these flawed practices by critiquing their use in a recent species distribution modeling technique developed for predicting Greater Sage-Grouse ( Centrocercus urophasianus ) distribution in Colorado, USA. These model averaging issues are common in other ecological literature and ought to be discontinued if we are to make effective scientific contributions to ecological knowledge and conservation of natural resources.

Ecology↗
USGS2012

Estimating risks to aquatic life using quantile regression

One of the primary goals of biological assessment is to assess whether contaminants or other stressors limit the ecological potential of running waters. It is important to interpret responses to contaminants relative to other environmental factors, but necessity or convenience limit quantification of all factors that influence ecological potential. In these situations, the concept of limiting factors is useful for data interpretation. We used quantile regression to measure risks to aquatic life exposed to metals by including all regression quantiles (τ = 0.05–0.95, by increments of 0.05), not just the upper limit of density (e.g., 90 th quantile). We measured population densities (individuals/0.1 m 2 ) of 2 mayflies (Rhithrogena spp., Drunella spp.) and a caddisfly (Arctopsyche grandis), aqueous metal mixtures (Cd, Cu, Zn), and other limiting factors (basin area, site elevation, discharge, temperature) at 125 streams in Colorado. We used a model selection procedure to test which factor was most limiting to density. Arctopsyche grandis was limited by other factors, whereas metals limited most quantiles of density for the 2 mayflies. Metals reduced mayfly densities most at sites where other factors were not limiting. Where other factors were limiting, low mayfly densities were observed despite metal concentrations. Metals affected mayfly densities most at quantiles above the mean and not just at the upper limit of density. Risk models developed from quantile regression showed that mayfly densities observed at background metal concentrations are improbable when metal mixtures are at US Environmental Protection Agency criterion continuous concentrations. We conclude that metals limit potential density, not realized average density. The most obvious effects on mayfly populations were at upper quantiles and not mean density. Therefore, we suggest that policy developed from mean-based measures of effects may not be as useful as policy based on the concept of limiting factors.

Colorado↗
USGS2012

Genetic and environmental influences on cold hardiness of native and introduced riparian trees

To explore latitudinal genetic variation in cold hardiness and leaf phenology, we planted a common garden of paired collections of native and introduced riparian trees sampled along a latitudinal gradient. The garden in Fort Collins, Colorado (latitude 40.6°N), included 681 native plains cottonwood (Populus deltoides subsp. monilifera) and introduced saltcedar (Tamarix ramosissima, T. chinensis, and hybrids) collected from 15 sites from 29.2 to 47.6°N in the central United States. In the common garden, both species showed latitudinal variation in fall, but not spring, leaf phenology. This suggests that latitudinal gradient field observations in fall phenology are a result, at least in part, of the inherited variation in the critical photoperiod. Conversely, the latitudinal gradient field observations in spring phenology are largely a plastic response to the temperature gradient. Populations from higher latitudes exhibited earlier bud set and leaf senescence. Cold hardiness varied latitudinally in both fall and spring for both species. Although cottonwood was hardier than saltcedar in midwinter, the reverse was true in late fall and early spring. The latitudinal variation in fall phenology and cold hardiness of saltcedar appears to have developed as a result of multiple introductions of genetically distinct populations, hybridization, and natural selection in the 150 years since introduction.

Conference Paper↗
USGS2011

Estimating geographic variation on allometric growth and body condition of blue suckers with quantile regression

Increasing our understanding of how environmental factors affect fish body condition and improving its utility as a metric of aquatic system health require reliable estimates of spatial variation in condition (weight at length). We used three statistical approaches that varied in how they accounted for heterogeneity in allometric growth to estimate differences in body condition of blue suckers Cycleptus elongatus across 19 large-river locations in the central USA. Quantile regression of an expanded allometric growth model provided the most comprehensive estimates, including variation in exponents within and among locations (range = 2.88–4.24). Blue suckers from more-southerly locations had the largest exponents. Mixed-effects mean regression of a similar expanded allometric growth model allowed exponents to vary among locations (range = 3.03–3.60). Mean relative weights compared across selected intervals of total length (TL = 510–594 and 594–692 mm) in a multiplicative model involved the implicit assumption that allometric exponents within and among locations were similar to the exponent (3.46) for the standard weight equation. Proportionate differences in the quantiles of weight at length for adult blue suckers (TL = 510, 594, 644, and 692 mm) compared with their average across locations ranged from 1.08 to 1.30 for southern locations (Texas, Mississippi) and from 0.84 to 1.00 for northern locations (Montana, North Dakota); proportionate differences for mean weight ranged from 1.13 to 1.17 and from 0.87 to 0.95, respectively, and those for mean relative weight ranged from 1.10 to 1.18 and from 0.86 to 0.98, respectively. Weights for fish at longer lengths varied by 600–700 g within a location and by as much as 2,000 g among southern and northern locations. Estimates for the Wabash River, Indiana (0.96–1.07 times the average; greatest increases for lower weights at shorter TLs), and for the Missouri River from Blair, Nebraska, to Sioux City, Iowa (0.90–1.00 times the average; greatest decreases for lower weights at longer TLs), were examined in detail to explain the additional information provided by quantile estimates.

Transactions of the American Fisheries Society↗