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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 [Te] and shaded [Ts]), ambient (Ta), subsurface ground (Th), and internal body (Tb) 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 Tb 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 (Te − Ta) 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 Tb of a population of wild, free‐ranging S. merianae over multiple biologically significant time periods and to associate Tb 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.

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.

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. published

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.

Lek disturbance buffers can be used to identify areas that provide important seasonal habitat for Gunnison sage grouse Centrocercus minimus (hereafter GUSG), a species with declining or vulnerable populations across their range. Lek disturbance buffers define areas around leks where anthropogenic disturbance is not permitted and have been considered for potential conservation strategies across GUSG habitat. Currently there is minimal information available on the effectiveness of the size of defined lek disturbance buffers. This study focused on two GUSG populations, the smaller Crawford population and a segment of the larger Gunnison Basin population. We utilized global positioning system location data on GUSG to evaluate seasonal use within three lek disturbance buffers, then compared and contrasted results between the two populations. The Crawford GUSG population showed increased movements from breeding season to late brood-rearing season and in winter returned to a usage pattern similar to the breeding season. Comparatively, the western Gunnison Basin GUSG population showed considerable movement throughout the entire year. In addition to these differences, we noted remarkable differences in distance between active leks, home range size, and total daily distance traveled between Crawford and western Gunnison Basin populations. Lek disturbance buffers created using the standard protocol provided varying protection depending on the distance between leks and number of leks. In small populations, the disturbance buffers overlapped each other, thus producing a smaller total lek disturbance buffer area. In addition to adding to the general body of knowledge of a little-studied species, our study had two important findings: 1) the use of empirical cumulative distribution demonstrated considerable differences in lek disturbance buffer use between the Crawford and the western Gunnison Basin populations, and 2) lek disturbance buffers did not provide equal protection for all populations on the basis of their current definition and derivation. We anticipate that land managers will find our results useful and informative when developing land management plans for the conservation of GUSG. Our analysis showed that the variability between populations and species is important for managers to consider when developing conservation strategies, especially for small populations.

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...

We tested the efficacy of 2 formulations of the immunocontraceptive SpayVac®, 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 = 30 each yr) were 100%, 96.7%, and 100%. In the nonaqueous treatment group, fertility was 16.7% in the first year (n = 30) and 75.9% in the second year (n = 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 = 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 + 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 domainin the USA.

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⋅ha(-1)⋅y(-1), we found a unimodal relationship; richness increased at low deposition levels and decreased above 8.7 and 13.4 kg N⋅ha(-1)⋅y(-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.

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.

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.

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.

This chapter aims to give a sense of the breadth of applications of quantile regression in ecology and the environmental sciences. It examines in greater detail the models, inferences, and interpretations for applications. Initial interest in quantile regression in ecology was primarily motivated by the desire to model boundary-type relationships between variables to provide an interpretation consistent with the concept of limiting factors based on Liebig's law of the minimum. The chapter provides additional estimates for multiple sites within a watershed to examine differences occurring within a watershed. It demonstrates the use of a censored quantile regression estimator that provides a generalization of the Kaplan–Meier estimator to linear models. As the application on water quality trends demonstrated, the ability to use nonlinear transformations with linear quantile regression to model inherently nonlinear, multiplicative relationships without any of the bias-correcting adjustments needed for modeling means in this same framework is a great advantage for ecological and environmental modeling.

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 analyzed1500 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 kM0.01 day(-1)) and are moderately hydrophobic (log KOW 6-8). 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 KOW and kM. Probability is greatest (∼100%) for slowly metabolized compounds, regardless of KOW, and lowest for chemicals with rapid transformation rates (kM0.2 day(-1)). This probabilistic model provides a new global tool for screening existing and new OCs for their biomagnification potential.

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., 90th quantile). We measured population densities (individuals/0.1 m2) 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 lim...

Equivalence estimated with linear quantile regression was used to evaluate compliance with habitat management objectives at Arapaho National Wildlife Refuge based on monitoring data collected in upland (5,781 ha; n = 511 transects) and riparian and meadow (2,856 ha, n = 389 transects) habitats from 2005 to 2008. Quantiles were used because the management objectives specified proportions of the habitat area that needed to comply with vegetation criteria. The linear model was used to obtain estimates that were averaged across 4 y. The equivalence testing framework allowed us to interpret confidence intervals for estimated proportions with respect to intervals of vegetative criteria (equivalence regions) in either a liberal, benefit-of-doubt or conservative, fail-safe approach associated with minimizing alternative risks. Simple Boolean conditional arguments were used to combine the quantile equivalence results for individual vegetation components into a joint statement for the multivariable management objectives. For example, management objective 2A required at least 809 ha of upland habitat with a shrub composition ≥0.70 sagebrush (Artemisia spp.), 20–30% canopy cover of sagebrush ≥25 cm in height, ≥20% canopy cover of grasses, and ≥10% canopy cover of forbs on average over 4 y. Shrub composition and canopy cover of grass each were readily met on >3,000 ha under either conservative or liberal interpretations of sampling variability. However, there were only 809–1,214 ha (conservative to liberal) with ≥10% forb canopy cover and 405–1,098 ha with 20–30% canopy cover of sagebrush ≥25 cm in height. Only 91–180 ha of uplands simultaneously met criteria for all four components, primarily because canopy cover of sagebrush and forbs was inversely related when considered at the spatial scale (30 m) of a sample transect. We demonstrate how the quantile equivalence analyses also can help refine the numerical specification of habitat objectives and explore specification of spatial scales for objectives with respect to sampling scales used to evaluate those objectives.

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...

Locally abundant feral horses (Equus caballus) can rapidly deplete available resources. Fertility control agents present promising nonlethal tools for reducing their population growth rates. We tested the effect of 2 forms of the immunocontraceptive porcine zona pellucida (PZP) on foaling rates in 3 populations of feral horses in the western United States. A liquid form requiring annual boosters was administered at Little Book Cliffs Wild Horse Range, Mesa County (CO), and Pryor Mountain Wild Horse Range, Bighorn County (WY) and Carbon County (MT), and a time-release pellet form designed to produce 2 yr of infertility was administered at McCullough Peaks Herd Management Area, Park County (WY). Average foaling rates (foals born/mare-yr) from direct observation of untreated and treated female horses (mares), 2004–2008, were 60.1% (n = 153 mare-yr) versus 6.6% (n = 91 mare-yr) at Little Book Cliffs, and 62.8% (n = 129 mare-yr) versus 17.7% (n = 79 mare-yr) at Pryor Mountain, respectively. At McCullough Peaks, mean annual foaling rates from 2006 to 2008 were 75.0% (n = 48 mare-yr) for untreated mares and 31.7% (n = 101 mare-yr) for treated mares. Controlling for age of mares and pretreatment differences in fertility, PZP reduced foaling rates in all 3 herds. The pellets used at McCullough Peaks (produced by cold evaporation) were less effective than pellets used in a previous trial and produced by heat extrusion. Immunocontraception with PZP may be a useful tool in reducing fertility rates in some western United States feral horse herds, but population growth reduction will depend on timely access to mares for inoculation and the proportion of mares that can be successfully treated. Published 2011. This article is a U.S. Government work and is in the public domain in the USA.

To explore the roles of plasticity and genetic variation in the response to spatial and temporal climate variation, we established a common garden consisting 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 at 29.2-47.6°N in the central United States. In the common garden both species showed latitudinal variation in fall, but not spring, leaf phenology, suggesting that the latitudinal gradient in fall phenology observed in the field results at least in part from inherited variation in the critical photoperiod, while the latitudinal gradient in spring phenology observed in the field is 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. For cottonwood, cold hardiness began earlier and ended later in northern than in southern populations. For saltcedar northern populations were hardier throughout the cold season than southern populations. 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.

Genetic diversity and species diversity are expected to covary according to area and isolation, but may not always covary with environmental heterogeneity. In this study, we examined how patterns of genetic and species diversity in stream fishes correspond to local and regional environmental conditions. To do so, we compared population size, genetic diversity and divergence in central stonerollers (Campostoma anomalum) to measures of species diversity and turnover in stream fish assemblages among similarly sized watersheds across an agriculture-forest land-use gradient in the Little Miami River basin (Ohio, USA). Significant correlations were found in many, but not all, pair-wise comparisons. Allelic richness and species richness were strongly correlated, for example, but diversity measures based on allele frequencies and assemblage structure were not. In-stream conditions related to agricultural land use were identified as significant predictors of genetic diversity and species diversity. Comparisons to population size indicate, however, that genetic diversity and species diversity are not necessarily independent and that variation also corresponds to watershed location and glaciation history in the drainage basin. Our findings demonstrate that genetic diversity and species diversity can covary in stream fish assemblages, and illustrate the potential importance of scaling observations to capture responses to hierarchical environmental variation. More comparisons according to life history variation could further improve understanding of conditions that give rise to parallel variation in genetic diversity and species diversity, which in turn could improve diagnosis of anthropogenic influences on aquatic ecosystems.

Summary 1. Organism–environment models are used widely in conservation. The degree to which they are useful for informing conservation decisions – the conservation relevance of these relations – is important because lack of relevance may lead to misapplication of scarce conservation resources or failure to resolve important conservation dilemmas. Even when models perform well based on model fit and predictive ability, conservation relevance of associations may not be clear without also knowing the magnitude and variability of predicted changes in response variables. 2. We introduce a method for evaluating the conservation relevance of organism–environment relations that employs confidence intervals for predicted changes in response variables. The confidence intervals are compared to a preselected magnitude of change that marks a threshold (trigger) for conservation action. To demonstrate the approach, we used a case study from the Chihuahuan Desert involving relations between avian richness and broad-scale patterns of shrubland. We considered relations for three winters and two spatial extents (1- and 2-km-radius areas) and compared predicted changes in richness to three thresholds (10%, 20% and 30% change). For each threshold, we examined 48 relations. 3. The method identified seven, four and zero conservation-relevant changes in mean richness for the 10%, 20% and 30% thresholds respectively. These changes were associated with major (20%) changes in shrubland cover, mean patch size, the coefficient of variation for patch size, or edge density but not with major changes in shrubland patch density. The relative rarity of conservation-relevant changes indicated that, overall, the relations had little practical value for informing conservation decisions about avian richness. 4. The approach we illustrate is appropriate for various response and predictor variables measured at any temporal or spatial scale. The method is broadly applicable across ecological environments, conservation objectives, types of statistical predictive models and levels of biological organization. By focusing on magnitudes of change that have practical significance, and by using the span of confidence intervals to incorporate uncertainty of predicted changes, the method can be used to help improve the effectiveness of conservation efforts.

Managers concerned with shrinking habitats and limited resources for wildlife seek effective tools for limiting population growth in some species. Fertility control is one such tool, yet little is known about its impacts on the behavioral ecology of wild, free-roaming animals. We investigated influences of the immunocontraceptive porcine zona pellucida (PZP) on individual and social behavior in bands of feral horses (Equus caballus) in three discrete populations and used 14 hierarchical mixed effect models to gain insight into the influences of PZP treatment on feral horse behavior. A model of body condition was the strongest predictor of feeding, resting, maintenance, and social behaviors, with treated females allocating their time similarly to control females. Time spent feeding declined 11.4% from low condition to high condition females (F1,154 = 26.427, P < 0.001) and was partially reciprocated by a 6.0% increase in resting (F1,154 = 7.629, P = 0.006), 0.9% increase in maintenance (F1,154 = 7.028, P = 0.009), and 1.8% increase in social behavior (F1,154 = 15.064, P < 0.001). There was no difference detected in body condition of treated versus control females (F1,154 = 0.033, P = 0.856), but females with a dependent foal had lower body condition than those without a foal (F1,154 = 4.512, P = 0.038). Herding behavior was best explained by a model of treatment and the interaction of band fidelity and foal presence (AICc weight = 0.660) which estimated no difference in rate of herding behavior directed toward control versus treated females (F1,102 = 0.196, P = 0.659), but resident females without a dependent foal were herded 50.9% more than resident females with a foal (F3,102 = 8.269, P < 0.001). Treated females received 54.5% more reproductive behaviors from stallions than control mares (F1,105 = 5.155, P = 0.025), with the model containing only treatment being the most-supported (AICc weight = 0.530). Treated and control females received harem-tending behaviors from stallions equally (F1,105 = 0.001, P = 0.969) and agonistic behaviors from stallions equally (F1,105 < 0.001, P = 0.986). Direct effects of PZP treatment on the behavior of feral horses appear to be limited primarily to reproductive behaviors and most other differences detected were attributed to the effects of body condition, band fidelity, or foal presence. PZP is a promising alternative to traditional hormone-based contraceptives and appears to contribute few short-term behavioral modifications in feral horses.

Assessment of emergent vegetation biomass can be time consuming and labor intensive. To establish a less onerous, yet accurate method, for determining emergent plant biomass than by direct measurements we collected vegetation data over a six-year period and modeled biomass using easily obtained variables: culm (stem) diameter, culm height and culm density. From 1998 through 2005, we collected emergent vegetation samples (Schoenoplectus californicus and Schoenoplectus acutus) at a constructed treatment wetland in San Jacinto, California during spring and fall. Various statistical models were run on the data to determine the strongest relationships. We found that the nonlinear relationship: $$ CB = {\beta _0}D{H^{{\beta _1}}}{10^\varepsilon } $$ , where CB was dry culm biomass (g m−2), DH was density of culms × average height of culms in a plot, and β0 and β1 were parameters to estimate, proved to be the best fit for predicting dried-live above-ground biomass of the two Schoenoplectus species. The random error distribution, e, was either assumed to be normally distributed for mean regression estimates or assumed to be an unspecified continuous distribution for quantile regression estimates.

Remotely sensed data represents key information for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance may allow us to quantitatively estimate how beta-diversity in species changes with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological datasets are characterized by a high number of zeroes that can add noise to the regression model. Quantile regression can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this paper, we used ordinary least square (OLS) and quantile regression to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p 0.05) considering both OLS and quantile regression. Nonetheless, OLS regression estimate of mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when spectral distance approaches zero, was very low compared with the intercepts of upper quantiles, which detected high species similarity when habitats are more similar. In this paper we demonstrated the power of using quantile regressions applied to spectral distance decay in order to reveal species diversity patterns otherwise lost or underestimated by ordinary least square regression.

Deuterium isotope analyses have revolutionized the study of migratory connectivity because global gradients of deuterium in precipitation (deltaD(P)) are expressed on a continental scale. Several authors have constructed continental scale base maps of deltaD(P) to provide a spatial reference for studying the movement patterns of migratory species and, although they are very useful, these maps present a static, 40-year average view of the landscape that ignores much underlying inter-annual variation. To more fully understand the consequences of this underlying variation, we analyzed the GNIP deuterium data, the source for all current deltaD(P) maps, to estimate the minimum separation in deltaD(P) (and latitude) necessary to conclude with a given level of confidence that distinct deltaD(P) values represent different geographic sites. Extending analyses of deltaD(P) successfully to deuterium in tissues of living organisms, e.g., feathers in migratory birds (deltaD(F)), is dependent on the existence of geographic separation of deltaD(P), where every geographic location has a distribution of values associated with temporal variability in deltaD(P). Analyses were conducted for three distinct geographic regions: North America, eastern North America (east of longitude 100 degrees W), and Argentina. At the 80% confidence level, the minimum separation values were 12, 7, and 14 degrees of latitude (equivalent to 53, 31, and 32 per thousand) for North America, eastern North America, and Argentina, respectively. Hence, in eastern North America, for example, one may not be able to accurately assign individual samples to sites separated by less than about 7 degrees of latitude as the distributions of deltaD(P) were not distinct at latitudes7 degrees apart. Moreover, two samples that differ by less than 31 per thousand cannot be confidently said to originate from different latitudes. These estimates of minimum separation for deltaD(P) do not include other known sources of variation in feather deuterium (deltaD(F)) and hence are a first order approximation that may be useful, in the absence of more specific information for the system of interest, for planning and interpreting the results of new stable isotope studies.

Many amphibians breed in water but live most of their lives in terrestrial habitats. Little is known, however, about the spatial distribution of these habitats or of the distances and directions amphibians move to reach breeding sites. The amphibian community at a small, temporary pond in northcentral Florida was monitored for 5 years. Based on captures and recaptures of more than 2500 striped newts (Notophthalmus perstriatus) and 5700 eastern narrow-mouthed toads (Gastrophryne carolinensis), we tabulated the angles of orientation that these amphibians entered and exited the pond basin. Our results showed that movements of these species between the pond and terrestrial habitats were nonrandom in orientation, but that narrow corridors did not appear to be used. Differences between the species likely reflect differences in habitat preferences, whereas intraspecific differences among years and between the sexes likely reflect variation among individuals. For terrestrial buffer zones to be effective at conserving pond-breeding amphibian communities, they need both a distance and a directional component. The determination of a directional component may be obscured if studies are carried out over a short time span. Conservation efforts for wetland-breeding amphibians that concentrate solely on the wetland likely will fail without consideration of the adjacent terrestrial habitat. Patrones de Movimiento y Conservacion de Anfibios en Humedales de Temporal Pequenos Muchos anfibios se reproducen en el agua pero viven la mayor parte de sus vidas en habitats terrestres. Sin embargo, poco se conoce sobre la distribucion espacial de estos habitats o de las distancias y direcciones en las que se mueven los anfibios para llegar a sus sitios de reproduccion. La comunidad de anfibios en estanques temporales pequenos en Florida nor-central ha sido monitoreada por 5 anos. En base a capturas y recapturas de mas de 2500 tritones rayados (Notophthalmus perstriatus) y 5700 sapos de boca chica del este (Gastrophryne carolinensis), tabulamos los angulos de orientacion en que estos anfibios entraron y salieron de la cuenca del estanque. Nuestros resultados muestran que los movimientos de estas especies entre el estanque y los habitats terrestres no tuvieron una orientacion azarosa, pero los corredores angostos aparentemente no son utilizados. Diferencias entre las especies parecen reflejar diferencias en las preferencias de habitat, mientras que diferencias intraespecificas entre anos y entre sexos parece reflejar variacion entre individuos. Para que las zonas terrestres de amortiguamiento sean efectivas en la conservacion de comunidades de reproductores de anfibios, necesitan tener como componentes una distancia y orientacion. La determinacion del compopente direccional puede ser obscurecido si los estudios se llevan a cabo en un periodo de tiempo corto. Los esfuerzos conservacionistas para anfibios de reproduccion en humedales tenderan a fallar si se concentran unicamente en el humedal sin tomor en consideracion el habitat terrestre adyacente.

Decomposition of senesced culm material of two bulrush species was studied in a surface-flow ammonia-dominated treatment wetland in southern California. Decomposition of the submerged culm material during summer months was relatively rapid (k = 0.037 day−1), but slowed under extended submergence (up to 245 days) and during fall and spring sampling periods (k = 0.009–0.014 day−1). Stepwise regression of seasonal data indicated that final water temperature and abundance of the culm-mining midge, Glyptotendipes, were significantly associated with culm decomposition. Glyptotendipes abundance, in turn, was correlated with water quality parameters such as conductivity and dissolved oxygen and ammonia concentrations. No differences were detected in decomposition rates between the bulrush species, Schoenoplectus californicus and Schoenoplectus acutus.

We used quantile regression to compare the body condition of walleye Sander vitreus and white bass Morone chrysops before (1980–1988) and after (1989–2004) the establishment of alewives Alosa pseudoharengus in Lake McConaughy, Nebraska. Higher quantiles (percentiles = 100% × quantiles (0, 1)) of weight (W) at the same total length (TL) were indicative of better body condition in an allometric growth model that included separate slopes and intercepts for the before and after groups. All quantiles of walleye weights by TL increased in the years after alewife introduction, ranging from 1.01 to 1.12 times weights in the years before alewife introduction, with greatest increases for the lower (

1. A quantile regression model for counts of breeding Cape Sable seaside sparrows Ammodramus maritimus mirabilis (L.) as a function of water depth and previous year abundance was developed based on extensive surveys, 1992-2005, in the Florida Everglades. The quantile count model extends linear quantile regression methods to discrete response variables, providing a flexible alternative to discrete parametric distributional models, e.g. Poisson, negative binomial and their zero-inflated counterparts. 2. Estimates from our multiplicative model demonstrated that negative effects of increasing water depth in breeding habitat on sparrow numbers were dependent on recent occupation history. Upper 10th percentiles of counts (one to three sparrows) decreased with increasing water depth from 0 to 30 cm when sites were not occupied in previous years. However, upper 40th percentiles of counts (one to six sparrows) decreased with increasing water depth for sites occupied in previous years. 3. Greatest decreases (-50% to -83%) in upper quantiles of sparrow counts occurred as water depths increased from 0 to 15 cm when previous year counts were 1, but a small proportion of sites (5-10%) held at least one sparrow even as water depths increased to 20 or 30 cm. 4. A zero-inflated Poisson regression model provided estimates of conditional means that also decreased with increasing water depth but rates of change were lower and decreased with increasing previous year counts compared to the quantile count model. Quantiles computed for the zero-inflated Poisson model enhanced interpretation of this model but had greater lack-of-fit for water depths > 0 cm and previous year counts 1, conditions where the negative effect of water depths were readily apparent and fitted better with the quantile count model.

We estimated abundance quantiles of redband trout Oncorhynchus mykiss gairdneri relative to five site-specific habitat variables (stream shading, bank cover, bank stability, fine sediment in the stream substrate, and cover for adults) and one landscape variable (distance from stream headwaters) on 30 streams in southwestern Idaho during 1993–1998. In addition, the five site-specific habitat variables were used to calculate a habitat suitability rating (HSR) used by the U.S. Bureau of Land Management to determine habitat quality of sagebrush desert streams for redband trout. Variation in abundance increased significantly with increasing HSR; the highest abundances were only found with high HSRs, indicating that the HSR model correctly predicted habitat quality for redband trout. However, a model that consisted of stream shade, distance from stream headwaters, and their interaction best predicted redband trout density, explaining 36% of the variation in adult density in sagebrush desert basin strea...

It is becoming more apparent that commonly used statistical methods (e.g., analysis of variance and regression) are not the best methods for estimating limiting relationships or stressor effects. A major challenge of estimating the effects associated with a measured subset of limiting factors is to account for the effects of unmeasured factors in an ecologically realistic matter. We used quantile regression to elucidate multiple stressor effects on end-of-season biomass data from two salt marsh sites in coastal Louisiana collected for 18 yr. Stressor effects evaluated based on available data were flooding, salinity, air temperature, cloud cover, precipitation deficit, grazing by muskrat, and surface water nitrogen and phosphorus. Precipitation deficit combined with surface water nitrogen provided the best two-parameter model to explain variation in the peak biomass with different slopes and intercepts for the two study sites. Precipitation deficit, cloud cover, and temperature were significantly correlated with each other. Surface water nitrogen was significantly correlated with surface water phosphorus and muskrat density. The site with the larger duration of flooding showed reduced peak biomass, when cloud cover and surface water nitrogen were optimal. Variation in the relatively low salinity occurring in our study area did not explain any of the variation in Spartina alterniflora biomass.

Performance of quantile rank score tests used for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1) were evaluated by simulation for models with p = 2 and 6 predictors, moderate collinearity among predictors, homogeneous and hetero-geneous errors, small to moderate samples (n = 20–300), and central to upper quantiles (0.50–0.99). Test statistics evaluated were the conventional quantile rank score T statistic distributed as χ2 random variable with q degrees of freedom (where q parameters are constrained by H 0:) and an F statistic with its sampling distribution approximated by permutation. The permutation F-test maintained better Type I errors than the T-test for homogeneous error models with smaller n and more extreme quantiles τ. An F distributional approximation of the F statistic provided some improvements in Type I errors over the T-test for models with > 2 parameters, smaller n, and more extreme quantiles but not as much improvement as the p...

We simulated the effects of missing information on statistical distributions of animal response that covaried with measured predictors of habitat to evaluate the utility and performance of quantile regression for providing more useful intervals of uncertainty in habitat relationships. These procedures were evaulated for conditions in which hetero­ geneity and hidden bias were induced by confounding with missing variables associated with other improtant processes, a problem common in statistical modeling of ecological phenomena. Simulations for a large (N � 10 000) finite population representing grid lo­ cations on a landscape demonstrated various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable. Quantile (0 � � � 1) regression parameters for linear models that excluded the important, unmeasured variable revealed bias relative to param­ eters from the generating model. Depending on whether interactions of the measured and unmeasured variables were negative (interference interactions) or positive (facilitation in­ teractions) in simulations without spatial structuring, either upper ( �� 0.5) or lower ( �� 0.5) quantile regression parameters were less biased than mean rate parameters. Hetero­ geneous, nonlinear response patterns occurred with correlations between the measured and unmeasured variables. When the unmeasured variable was spatially structured, variation in parameters across quantiles associated with heterogeneous effects of the habitat variable was reduced by modeling the spatial trend surface as a cubic polynomial of location co­ ordinates, but substantial hidden bias remained. Sampling (n � 20-300) simulations dem­ onstrated that regression quantile estimates and confidence intervals constructed by in­ verting weighted rank score tests provided valid coverage of these parameters. Local forms of quantile weighting were required for obtaining correct Type I error rates and confidence interval coverage. Quantile regression was used to estimate effects of physical habitat resources on a bivalve (Macomona liliana )i n the spatially structured landscape on a sandflat in a New Zealand harbor. Confidence intervals around predicted 0.10 and 0.90 quantiles were used to estimate sampling intervals containing 80% of the variation in densities in relation to bed elevation. Spatially structured variation in bivalve counts estimated by a cubic polynomial trend surface remained after accounting for the nonlinear effects of bed elevation, indicating the existence of important spatially structured processes that were not adequately represented by the measured habitat variables.

In 1990–1992, we studied predation of waterfowl nests by mammalian predators on 30 islands in a 64-km reach of the Snake River in southwestern Idaho, USA, to identify river flows necessary to protect and enhance migratory bird use of Deer Flat National Wildlife Refuge. We monitored 235–314 Canada goose (Branta canadensis) nests each year and 122 duck nests, primarily mallard (Anas platyrhynchos), in 1991. We calculated island isolation as the flow energy (width × average water velocity [m2/sec]) a predator encountered in crossing to an island. Density of goose nests increased as island isolation increased (P < 0.001). In contrast, visits of terrestrial predators to islands, mammalian predation of goose nests, and variance in predation rates decreased as island isolation increased (P < 0.01). Nests were most frequently depredated by raccoons (Procyon lotor), coyotes (Canis latrans), badgers (Taxidea taxus), and mink (Mustela vison). Multiple regression models explained 67% of the variance in nest ...

Quantile regression is a way to estimate the conditional quantiles of a response variable distribution in the linear model that provides a more complete view of possible causal relationships between variables in ecological processes. Typically, all the factors that affect ecological processes are not measured and included in the statistical models used to investigate relationships between variables associated with those processes. As a consequence, there may be a weak or no predictive relationship between the mean of the response variable (y) distribution and the measured predictive factors (X). Yet there may be stronger, useful predictive relationships with other parts of the response variable distribution. This primer relates quantile regression estimates to prediction intervals in parametric error distribution regression models (eg least squares), and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of the estimates for homogeneous and heterogen...

We used regression quantiles to model potentially limiting relationships between the standing crop of cutthroat trout Oncorhynchus clarki and measures of stream channel morphology. Regression quantile models indicated that variation in fish density was inversely related to the width:depth ratio of streams but not to stream width or depth alone. The spatial and temporal stability of model predictions were examined across years and streams, respectively. Variation in fish density with width:depth ratio (10th-90th regression quantiles) modeled for streams sampled in 1993-1997 predicted the variation observed in 1998-1999, indicating similar habitat relationships across years. Both linear and nonlinear models described the limiting relationships well, the latter performing slightly better. Although estimated relationships were transferable in time, results were strongly dependent on the influence of spatial variation in fish density among streams. Density changes with width:depth ratio in a single st...

Rates of change in final summer densities of two desert annuals, Eriogonum abertianum and Haplopappus gracilis, as constrained by their initial winter germination densities were estimated with regression quantiles and compared with mechanistic fits based on a self-thinning rule proposed by Guo et al. (1998); Oikos 83: 237-245). The allometric relation used was equivalent to S = Nf (N i ) -1 = c f (N i ) - , where S is the ratio of final to initial densities (survivorship), c f is a constant that is a final density specific to the species and environment, N f is the initial plant density, and N f is final plant density. We used regression quantiles to estimate c f assuming the exponent of - 1 was fixed (model 1, N f (N f ) -1 = c f (N i ) -1 and also obtained estimates by treating the exponent as a parameter to estimate (model 2, N f (N f )- = c f (N i ) λ ). Regression quantiles allow rates of change to be estimated through any part of a data distribution conditional on some linear function of covariates. We focused on estimates for upper (90-99th) quantiles near the boundary of the summer density distributions where we expected effects of self-thinning to operate as the primary constraint on plant performance. Allometric functions estimated with regression quantiles were similar to functions fit by Guo et al. (1998) when the exponent was constrained to - 1. However, the data were more consistent with estimates for model (2), where exponents were closer to - 0.4 than - 1, although model fit was not as good at higher initial plant densities as when the exponent was fixed at - 1. An exponential form (model 3, N f (N i ) -1 = c f (N i ) λNi ) that is a generalization of the discrete logistic growth function, where estimates of λ were - 0.23 to - 0.28 and estimates of γ were - 0.003 to - 0.006, provided better fit from low to high initial germination densities. Model 3 predictions were consistent with an interpretation that final summer densities were constrained by initial germination densities when these were low ( < 40 per 0.25 m 2 for Eriogonum and < 100 per 0.25 m 2 for Haplopappus) and were constrained by the self-thinning process at higher germination densities. Our exponential model (3) estimated with regression quantiles had similar form to the mechanistic relation of Guo et al. (1998) when plotted as a survivorship function, but avoided the unrealistic assumption that all populations attained a similar final density, and was based on a statistical model that has formal rules for estimation and inference.

In a recent Concepts paper in Ecology, Thomson et al. emphasized that assumptions of conventional correlation and regression analyses fundamentally conflict with the ecological concept of limiting factors, and they called for new statistical procedures to address this problem. The analytical issue is that unmeasured factors may be the active limiting constraint and may induce a pattern of unequal variation in the biological response variable through an interaction with the measured factors. Consequently, changes near the maxima, rather than at the center of response distributions, are better estimates of the effects expected when the observed factor is the active limiting constraint. Regression quantiles provide estimates for linear models fit to any part of a response distribution, including near the upper bounds, and require minimal assumptions about the form of the error distribution. Regression quantiles extend the concept of one-sample quantiles to the linear model by solving an optimization problem ...

A wedge-shaped pattern of variation in stream fish standing stock estimates relative to a habitat variable, in which range of standing stocks increases as a function of the variable, is consistent with the concept that the habitat variable is a limiting factor for fish populations. This pattern of variation complicates interpretation of parameter estimates and significance of ordinary least-squares (OLS) regression models of conditional mean standing stock; slopes of these regression models may have little or no relation to slopes of models describing standing stock limits. We modeled standing stock limits by testing for homoscedastic error distributions, screening plots of coordinate pairs for evidence of a wedge-shaped pattern of data, and estimating 90th regression quantiles for simple linear models. Application of this technique to data sets supporting 35 previously published OLS regression models of stream fish standing stocks led to rejection of homoscedasticity (P < 0.10) in 13 of the 35 d...

We investigated polychlorinated biphenyl (PCB) bioaccumulation relative to octanol-water partition coefficient (K(OW)) and organism trophic position (TP) at the Lake Hartwell Superfund site (South Carolina). We measured PCBs (127 congeners) and stable isotopes (δ¹⁵N) in sediment, organic matter, phytoplankton, zooplankton, macroinvertebrates, and fish. TP, as calculated from δ¹⁵N, was significantly, positively related to PCB concentrations, and food web trophic magnification factors (TMFs) ranged from 1.5-6.6 among congeners. TMFs of individual congeners increased strongly with log K(OW), as did the predictive power (r²) of individual TP-PCB regression models used to calculate TMFs. We developed log K(OW)-TMF models for eight food webs with vastly different environments (freshwater, marine, arctic, temperate) and species composition (cold- vs warmblooded consumers). The effect of K(OW) on congener TMFs varied strongly across food webs (model slopes 0.0-15.0) because the range of TMFs among studies was also highly variable. We standardized TMFs within studies to mean = 0, standard deviation (SD) = 1 to normalize for scale differences and found a remarkably consistent K(OW) effect on TMFs (no difference in model slopes among food webs). Our findings underscore the importance of hydrophobicity (as characterized by K(OW)) in regulating bioaccumulation of recalcitrant compounds in aquatic systems, and demonstrate that relationships between chemical K(OW) and bioaccumulation from field studies are more generalized than previously recognized.

Estimation of lean mass and lipid levels in birds involves the derivation of predictive equations that relate morphological measurements and, more recently, total body electrical conductivity (TOBEC) indices to known lean and lipid masses. Using cross-validation techniques, we evaluated the ability of several published and new predictive equations to estimate lean and lipid mass of Semipalmated Sandpipers (Calidris pusilla) and White-rumped Sandpipers (C. fuscicollis). We also tested ideas of Morton et al. (1991), who stated that current statistical approaches to TOBEC methodology misrepresent precision in estimating body fat. Three published interspecific equations using TOBEC indices predicted lean and lipid masses of our sample of birds with average errors of 8-28% and 53-155%, respectively. A new two-species equation relating lean mass and TOBEC indices revealed average errors of 4.6% and 23.2% in predicting lean and lipid mass, respectively. New intraspecific equations that estimate lipid mass directly from body mass, morphological measurements, and TOBEC indices yielded about a 13% error in lipid estimates. Body mass and morphological measurements explained a substantial portion of the variance (about 90%) in fat mass of both species. Addition of TOBEC indices improved the predictive model more for the smaller than for the larger sandpiper. TOBEC indices explained an additional 7.8% and 2.6% of the variance in fat mass and reduced the minimum breadth of prediction intervals by 0.95 g (32%) and 0.39 g (13%) for Semipalmated and White-rumped Sandpipers, respectively. The breadth of prediction intervals for models used to predict fat levels of individual birds must be considered when interpreting the resultant lipid estimates.