Geology topics

William L. Kendall

Publications and source records attributed to William L. Kendall.

At least 55 records · Page 3Linked to original sources

USGS2016

Overwintering strategies of migratory birds: a novel approach for estimating seasonal movement patterns of residents and transients

Our understanding of movement patterns in wildlife populations has played an important role in current ecological knowledge and can inform landscape conservation decisions. Direct measures of movement can be obtained using marked individuals, but this requires tracking individuals across a landscape or multiple sites. We demonstrate how movements can be estimated indirectly using single-site, capture–mark–recapture (CMR) data with a multi-state open robust design with state uncertainty model (MSORD-SU). We treat residence and transience as two phenotypic states of overwintering migrants and use time- and state-dependent probabilities of site entry and persistence as indirect measures of movement. We applied the MSORD-SU to data on eight species of overwintering Neotropical birds collected in 14 countries between 2002 and 2011. In addition to entry and persistence probabilities, we estimated the proportions of residents at a study site and mean residence times. We identified overwintering movement patterns and residence times that contrasted with prior categorizations of territoriality. Most species showed an evidence of residents entering sites at multiple time intervals, with transients tending to enter between peak resident movement times. Persistence and the proportion of residents varied by latitude, but were not always positively correlated for a given species. Synthesis and applications . Our results suggest that migratory songbirds commonly move among habitats during the overwintering period. Substantial proportions of populations appear to be comprised of transient individuals, and residents tend to persist at specific sites for relatively short periods of time. This information on persistence and movement patterns should be explored for specific habitats to guide landscape management on the wintering grounds, such as determining which habitats are conserved or restored as part of certification programmes of tropical agroforestry crops. We suggest that research and conservation efforts on Neotropical migrant songbirds focus on identifying landscape configurations and regional habitat networks that support these diverse overwintering strategies to secure full life cycle conservation.

Journal of Applied Ecology↗

USGS2016

Considering transient population dynamics in the conservation of slow life-history species: An application to the sandhill crane

The importance of transient dynamics of structured populations is increasingly recognized in ecology, yet these implications are not largely considered in conservation practices. We investigate transient and long-term population dynamics to demonstrate the process and utility of incorporating transient dynamics into conservation research and to better understand the population management of slow life-history species; these species can be theoretically highly sensitive to short- and long-term transient effects. We are specifically interested in the effects of anthropogenic removal of individuals from populations, such as caused by harvest, poaching, translocation, or incidental take. We use the sandhill crane ( Grus canadensis ) as an exemplar species; it is long-lived, has low reproduction, late maturity, and multiple populations are subject to sport harvest. We found sandhill cranes to have extremely high potential, but low likelihood for transient dynamics, even when the population is being harvested. The typically low population growth rate of slow life-history species appears to buffer against many perturbations causing large transient effects. Transient dynamics will dominate population trajectories of these species when stage structures are highly biased towards the younger and non-reproducing individuals, a situation that may be rare in established populations of long-lived animals. However, short-term transient population growth can be highly sensitive to vital rates that are relatively insensitive under equilibrium, suggesting that stage structure should be known if perturbation analysis is used to identify effective conservation strategies. For populations of slow life-history species that are not prone to large perturbations to their most productive individuals, population growth may be approximated by equilibrium dynamics.

Biological Conservation↗

USGS2016

Tradeoffs between physical captures and PIT tag antenna array detections: A case study for the Lower Colorado River Basin population of humpback chub ( Gila cypha )

A key component of many monitoring programs for special status species involves capture and handling of individuals as part of capture-recapture efforts for tracking population health and demography. Minimizing negative impacts from sampling, such as through reduced handling, aids prevention of negative impacts on species from monitoring efforts. Using simulation analyses, we found that long-term population monitoring techniques, requiring physical capture (i.e. hoop-net sampling), can be reduced and supplemented with passive detections (i.e. PIT tag antenna array detections) without negatively affecting estimates of adult humpback chub (HBC; Gila cypha ) survival ( S ) and skipped spawning probabilities (γ' = spawner transitions to a skipped spawner, γ′ = skipped spawner remains a skipped spawner). Based on our findings of the array’s in situ detection efficiency (0.42), estimability of such demographic parameters would improve over hoop-netting alone. In addition, the array provides insight into HBC population dynamics and movement patterns outside of traditional sampling periods. However, given current timing of sampling efforts, spawner abundance estimates were negatively biased when hoop-netting was reduced, suggesting not all spawning HBC are present during the current sampling events. Despite this, our findings demonstrate that PIT tag antenna arrays, even with moderate potential detectability, may allow for reduced handling of special status species while also offering potentially more efficient monitoring strategies, especially if ideal timing of sampling can be determined.

Arizona↗

USGS2015

Population size and stopover duration estimation using mark–resight data and Bayesian analysis of a superpopulation model

We present a novel formulation of a mark–recapture–resight model that allows estimation of population size, stopover duration, and arrival and departure schedules at migration areas. Estimation is based on encounter histories of uniquely marked individuals and relative counts of marked and unmarked animals. We use a Bayesian analysis of a state–space formulation of the Jolly–Seber mark–recapture model, integrated with a binomial model for counts of unmarked animals, to derive estimates of population size and arrival and departure probabilities. We also provide a novel estimator for stopover duration that is derived from the latent state variable representing the interim between arrival and departure in the state–space model. We conduct a simulation study of field sampling protocols to understand the impact of superpopulation size, proportion marked, and number of animals sampled on bias and precision of estimates. Simulation results indicate that relative bias of estimates of the proportion of the population with marks was low for all sampling scenarios and never exceeded 2%. Our approach does not require enumeration of all unmarked animals detected or direct knowledge of the number of marked animals in the population at the time of the study. This provides flexibility and potential application in a variety of sampling situations (e.g., migratory birds, breeding seabirds, sea turtles, fish, pinnipeds, etc.). Application of the methods is demonstrated with data from a study of migratory sandpipers.

Biometrics↗

USGS2015

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations

Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring–summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.

Journal of Animal Ecology↗

USGS2015

Testing hypotheses on distribution shifts and changes in phenology of imperfectly detectable species

With ongoing climate change, many species are expected to shift their spatial and temporal distributions. To document changes in species distribution and phenology, detection/non-detection data have proven very useful. Occupancy models provide a robust way to analyse such data, but inference is usually focused on species spatial distribution, not phenology. We present a multi-season extension of the staggered-entry occupancy model of Kendall et al . (2013, Ecology , 94, 610), which permits inference about the within-season patterns of species arrival and departure at sampling sites. The new model presented here allows investigation of species phenology and spatial distribution across years, as well as site extinction/colonization dynamics. We illustrate the model with two data sets on European migratory passerines and one data set on North American treefrogs. We show how to derive several additional phenological parameters, such as annual mean arrival and departure dates, from estimated arrival and departure probabilities. Given the extent of detection/non-detection data that are available, we believe that this modelling approach will prove very useful to further understand and predict species responses to climate change.

Methods in Ecology and Evolution↗

USGS2015

Life-history tradeoffs and reproductive cycles in Spotted Owls

The study of tradeoffs among life-history traits has long been key to understanding the evolution of life-history strategies. However, more recently, evolutionary ecologists have realized that reproductive costs have the potential to influence population dynamics. Here, we tested for costs of reproduction in the California Spotted Owl ( Strix occidentalis occidentalis ), and assessed whether costs of reproduction in year t − 1 on reproduction in year t could be responsible for regionally synchronized biennial cycles in reproductive output. Logistic regression analysis and multistate mark–recapture models with state uncertainty revealed that breeding reduced the likelihood of reproducing in the subsequent year by 16% to 38%, but had no influence on subsequent survival. We also found that costs of reproduction in year t − 1 were correlated with climatic conditions in year t , with evidence of higher costs during the dry phase of the El Niño–Southern Oscillation. Using a simulation-based population model, we showed that strong reproductive costs had the potential to create biennial cycles in population-level reproductive output; however, estimated costs of reproduction appeared to be too small to explain patterns observed in Spotted Owls. In the absence of strong reproductive costs, we hypothesize that observed natural cycles in the reproductive output of Spotted Owls are related to as-yet-unmeasured, regionally concordant fluctuations in environmental conditions or prey resources. Despite theoretical evidence for demographic effects, our analyses illustrate that linking tradeoffs to actual changes in population processes will be challenging because of the potential confounding effects of individual and environmental variation.

The Auk↗

USGS2015

Population trends and survival of nesting green sea turtles Chelonia mydas on Aves Island, Venezuela

Long-term demographic data are valuable for assessing the effect of anthropogenic impacts on endangered species and evaluating recovery programs. Using a 2-state open robust design model, we analyzed mark-recapture data from green turtles Chelonia mydas sighted between 1979 and 2009 on Aves Island, Venezuela, a rookery heavily impacted by human activities before it was declared a wildlife refuge in 1972. Based on the encounter histories of 7689 nesting females, we estimated the abundance, annual survival, and remigration intervals for this population. Female survival varied from 0.14-0.91, with a mean of 0.79, which is low compared to survival of other populations from the Caribbean (mean = 0.84) and Australia (mean = 0.95), even though we partially corrected for tag loss, which is known to negatively bias survival estimates. This supports prior suggestions that Caribbean populations in general, and the Aves Island population in particular, may be more strongly impacted than populations elsewhere. It is likely that nesters from this rookery are extracted while foraging in remote feeding grounds where hunting still occurs. Despite its relatively low survival, the nesting population at Aves Island increased during the past 30 years from approx. 500 to >1000 nesting females in 2009. Thus, this population, like others in the Caribbean and the Atlantic, seems to be slowly recovering following protective management. Although these findings support the importance of long-term conservation programs aimed at protecting nesting grounds, they also highlight the need to extend management actions to foraging grounds where human activities may still impact green turtle populations.

Aves Island↗

USGS2014

Increased flexibility for modeling telemetry and nest-survival data using the multistate framework

Although telemetry is one of the most common tools used in the study of wildlife, advances in the analysis of telemetry data have lagged compared to progress in the development of telemetry devices. We demonstrate how standard known-fate telemetry and related nest-survival data analysis models are special cases of the more general multistate framework. We present a short theoretical development, and 2 case examples regarding the American black duck and the mallard. We also present a more complex lynx data analysis. Although not necessary in all situations, the multistate framework provides additional flexibility to analyze telemetry data, which may help analysts and biologists better deal with the vagaries of real-world data collection.

Journal of Wildlife Management↗

USGS2014

Reducing bias in survival under non-random temporary emigration

Despite intensive monitoring, temporary emigration from the sampling area can induce bias severe enough for managers to discard life-history parameter estimates toward the terminus of the times series (terminal bias). Under random temporary emigration unbiased parameters can be estimated with CJS models. However, unmodeled Markovian temporary emigration causes bias in parameter estimates and an unobservable state is required to model this type of emigration. The robust design is most flexible when modeling temporary emigration, and partial solutions to mitigate bias have been identified, nonetheless there are conditions were terminal bias prevails. Long-lived species with high adult survival and highly variable non-random temporary emigration present terminal bias in survival estimates, despite being modeled with the robust design and suggested constraints. Because this bias is due to uncertainty about the fate of individuals that are undetected toward the end of the time series, solutions should involve using additional information on survival status or location of these individuals at that time. Using simulation, we evaluated the performance of models that jointly analyze robust design data and an additional source of ancillary data (predictive covariate on temporary emigration, telemetry, dead recovery, or auxiliary resightings) in reducing terminal bias in survival estimates. The auxiliary resighting and predictive covariate models reduced terminal bias the most. Additional telemetry data was effective at reducing terminal bias only when individuals were tracked for a minimum of two years. High adult survival of long-lived species made the joint model with recovery data ineffective at reducing terminal bias because of small-sample bias. The naïve constraint model (last and penultimate temporary emigration parameters made equal), was the least efficient, though still able to reduce terminal bias when compared to an unconstrained model. Joint analysis of several sources of data improved parameter estimates and reduced terminal bias. Efforts to incorporate or acquire such data should be considered by researchers and wildlife managers, especially in the years leading up to status assessments of species of interest. Simulation modeling is a very cost effective method to explore the potential impacts of using different sources of data to produce high quality demographic data to inform management.

Ecological Applications↗

USGS2014

Environmental correlates of temporary emigration for female Weddell seals and consequences for recruitment

In colonial-breeding species, prebreeders often emigrate temporarily from natal reproductive colonies then subsequently return for one or more years before producing young. Variation in attendance–nonattendance patterns can have implications for subsequent recruitment. We used open robust-design multistate models and 28 years of encounter data for prebreeding female Weddell seals ( Leptonychotes weddellii [Lesson]) to evaluate hypotheses about (1) the relationships of temporary emigration (TE) probabilities to environmental and population size covariates and (2) motivations for attendance and consequences of nonattendance for subsequent probability of recruitment to the breeding population. TE probabilities were density dependent (β&circ; BPOP = 0.66, = 0.17; estimated effects [β] and standard errors of population size in the previous year) and increased when the fast-ice edge was distant from the breeding colonies (β&circ; DIST = 0.75, = 0.04; estimated effects and standard errors of distance to the sea-ice edge in the current year on TE probability in the current year) and were strongly age and state dependent. These results suggest that trade-offs between potential benefits and costs of colony attendance vary annually and might influence motivation to attend colonies. Recruitment probabilities were greatest for seals that consistently attended colonies in two or more years (e.g., = 0.56, SD = 0.17) and lowest for seals that never or inconsistently attended prior to recruitment (e.g., = 0.32, SD = 0.15), where denotes the mean recruitment probability (over all years) for 10-year-old seals for the specified prebreeder state. In colonial-breeding seabirds, repeated colony attendance increases subsequent probability of recruitment to the adult breeding population; our results suggest similar implications for a marine mammal and are consistent with the hypothesis that prebreeders were motivated to attend reproductive colonies to gain reproductive skills or perhaps to optimally synchronize estrus through close association with mature breeding females.

Ecology↗

USGS2013

Capture-recapture methodology

Capture-recapture methods were initially developed to estimate human population abundance, but since that time have seen widespread use for fish and wildlife populations to estimate and model various parameters of population, metapopulation, and disease dynamics. Repeated sampling of marked animals provides information for estimating abundance and tracking the fate of individuals in the face of imperfect detection. Mark types have evolved from clipping or tagging to use of noninvasive methods such as photography of natural markings and DNA collection from feces. Survival estimation has been emphasized more recently as have transition probabilities between life history states and/or geographical locations, even where some states are unobservable or uncertain. Sophisticated software has been developed to handle highly parameterized models, including environmental and individual covariates, to conduct model selection, and to employ various estimation approaches such as maximum likelihood and Bayesian approaches. With these user-friendly tools, complex statistical models for studying population dynamics have been made available to ecologists. The future will include a continuing trend toward integrating data types, both for tagged and untagged individuals, to produce more precise and robust population models.

Book chapter↗

USGS2013

Relaxing the closure assumption in single-season occupancy models: staggered arrival and departure times

Occupancy statistical models that account for imperfect detection have proved very useful in several areas of ecology, including species distribution and spatial dynamics, disease ecology, and ecological responses to climate change. These models are based on the collection of multiple samples at each of a number of sites within a given season, during which it is assumed the species is either absent or present and available for detection while each sample is taken. However, for some species, individuals are only present or available for detection seasonally. We present a statistical model that relaxes the closure assumption within a season by permitting staggered entry and exit times for the species of interest at each site. Based on simulation, our open model eliminates bias in occupancy estimators and in some cases increases precision. The power to detect the violation of closure is high if detection probability is reasonably high. In addition to providing more robust estimation of occupancy, this model permits comparison of phenology across sites, species, or years, by modeling variation in arrival or departure probabilities. In a comparison of four species of amphibians in Maryland we found that two toad species arrived at breeding sites later in the season than a salamander and frog species, and departed from sites earlier.

Ecology↗

USGS2012

Maximizing the utility of monitoring to the adaptive management of natural resources

Data collection is an important step in any investigation about the structure or processes related to a natural system. In a purely scientific investigation (experiments, quasi-experiments, observational studies), data collection is part of the scientific method, preceded by the identification of hypotheses and the design of any manipulations of the system to test those hypotheses. Data collection and the manipulations that precede it are ideally designed to maximize the information that is derived from the study. That is, such investigations should be designed for maximum power to evaluate the relative validity of the hypotheses posed. When data collection is intended to inform the management of ecological systems, we call it monitoring. Note that our definition of monitoring encompasses a broader range of data-collection efforts than some alternative definitions – e.g. Chapter 3. The purpose of monitoring as we use the term can vary, from surveillance or “thumb on the pulse” monitoring (see Nichols and Williams 2006), intended to detect changes in a system due to any non-specified source (e.g. the North American Breeding Bird Survey), to very specific and targeted monitoring of the results of specific management actions (e.g. banding and aerial survey efforts related to North American waterfowl harvest management). Although a role of surveillance monitoring is to detect unanticipated changes in a system, the same result is possible from a collection of targeted monitoring programs distributed across the same spatial range (Box 4.1). In the face of limited budgets and many specific management questions, tying monitoring as closely as possible to management needs is warranted (Nichols and Williams 2006). Adaptive resource management (ARM; Walters 1986, Williams 1997, Kendall 2001, Moore and Conroy 2006, McCarthy and Possingham 2007, Conroy et al. 2008a) provides a context and specific purpose for monitoring: to evaluate decisions with respect to achievement of specific management objectives; and to evaluate the relative validity of predictive system models. This latter purpose is analogous to the role of data collection within the scientific method, in a research context.

Book chapter↗

USGS2012

Estimating parameters of hidden Markov models based on marked individuals: use of robust design data

Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last twenty years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We also provide user-friendly software to implement these models. This general framework could also be used by practitioners to consider constrained models of particular interest, or model the relationship between within-primary period parameters (e.g., state structure) and between-primary period parameters (e.g., state transition probabilities).

Ecology↗

USGS2012

Extreme weather and experience influence reproduction in an endangered bird

Extreme weather events, such as droughts and heat waves, are expected to become more severe and more frequent in the coming years, and understanding their impacts on demographic rates is of increasing interest to both evolutionary ecologists and conservation practitioners. An individual's breeding probability can be a sensitive indicator of the decision to initiate reproductive behavior under varying environmental conditions, has strong fitness consequences, and can be considered the first step in a life history trade-off between allocating resources for breeding activities or self-survival. Using a 14-year time series spanning large variation in climatic conditions and the entirety of a population's breeding range, we estimated the effects of extreme weather conditions (drought) on the state-specific probabilities of breeding and survival of an endangered bird, the Florida Snail Kite ( Rostrhamus sociabilis plumbeus ). Our analysis accounted for uncertainty in breeding status assignment, a common source of uncertainty that is often ignored when states are based on field observations. Breeding probabilities in adult kites (>1 year of age) decreased during droughts, whereas the probability of breeding in young kites (1 year of age) tended to increase. Individuals attempting to breed showed no evidence of reduced future survival. Although population viability analyses of this species and other species often implicitly assume that all adults will attempt to breed, we find that breeding probabilities were significantly <1 for all 13 estimable years considered. Our results suggest that experience is an important factor determining whether or not individuals attempt to breed during harsh environmental conditions and that reproductive effort may be constrained by an individual's quality and/or despotic behavior among individuals attempting to breed.

Florida↗

USGS2011

Monitoring bald eagles using lists of nests: Response to Watts and Duerr

The post-delisting monitoring plan for bald eagles ( Haliaeetus leucocephalus ) roposed use of a dual-frame sample design, in which sampling of known nest sites in combination with additional area-based sampling is used to estimate total number of nesting bald eagle pairs. Watts and Duerr (2010) used data from repeated observations of bald eagle nests in Virginia, USA to estimate a nest turnover rate and used this rate to simulate decline in number of occupied nests in list nests over time. Results of Watts and Duerr suggest that, given the rates of loss of nests from the list of known nest sites in Virginia, the list information will be of little value to sampling unless lists are constantly updated. Those authors criticize the plan for not placing sufficient emphasis on updating and maintaining lists of bald eagle nests. Watts and Duerr's metric of turnover rate does not distinguish detectability or temporary nonuse of nests from permanent loss of nests and likely overestimates turnover rate. We describe a multi-state capture–recapture model that allows appropriate estimation of rates of loss of nests, and we use the model to estimate rates of loss from a sample of nests from Maine, USA. The post-delisting monitoring plan addresses the need to maintain and update the lists of nests, and we show that dual frame sampling is an effective approach for sampling nesting bald eagle populations.

Virginia↗

USGS2011

Targeted surveillance for highly pathogenic avian influenza in migratory waterfowl across the conterminous United States: chapter 12

Introduction of Asian strain H5N1 Highly Pathogenic avian influenca via waterfowl migration is one potential route of entry into the United States. In conjunction with state, tribe, and laboratory partners, the United States Department of Agriculture collected and tested 124,603 wild bird samples in 2006 as part of a national surveillance effort. A sampling plan was devised to increase the probability fo detecting Asian strain H5N1 at a national scale. Band recovery data were used to identify and prioritize sampling for wild migratory waterfowl, resulting in spatially targeted sampling recommendations focused on reads with high numbers of recoveries. We also compared the spatial and temporal distribution of the 2006 cloacal and fecal waterfowl sampling effort to the bird banding recovery data and found concordance between the two .Finally, we present improvements made to the 2007 fecal sampling component of the surveillance plan and suggest further improvements for future sampling.

Book chapter↗