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Accounting for imperfect detection of groups and individuals when estimating abundance

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double-observer models, distance sampling models and combined double-observer and distance sampling models (known as mark-recapture-distance-sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under-counted, but not over-counted. The estimator combines an MRDS model with an N-mixture model to account for imperfect detection of individuals. The new MRDS-Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS-Nmix model to an MRDS model. Abundance estimates generated by the MRDS-Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re-allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.

Ecology and Evolution↗

Diel predator activity drives a dynamic landscape of fear

A “landscape of fear” (LOF) is a map that describes continuous spatial variation in an animal's perception of predation risk. The relief on this map reflects, for example, places that an animal avoids to minimize risk. Although the LOF concept is a potentially unifying theme in ecology that is often invoked to explain the ecological and conservation significance of fear, little is known about the daily dynamics of an LOF. Despite theory and data to the contrary, investigators often assume, implicitly or explicitly, that an LOF is a static consequence of a predator's mere presence within an ecosystem. We tested the prediction that an LOF in a large‐scale, free‐living system is a highly dynamic map with “peaks” and “valleys” that alternate across the diel (24‐h) cycle in response to daily lulls in predator activity. We did so with extensive data from the case study of Yellowstone elk ( Cervus elaphus ) and wolves ( Canis lupus ) that was the original basis for the LOF concept. We quantified the elk LOF, defined here as spatial allocation of time away from risky places and times, across nearly 1,000‐km 2 of northern Yellowstone National Park and found that it fluctuated with the crepuscular activity pattern of wolves, enabling elk to use risky places during wolf downtimes. This may help explain evidence that wolf predation risk has no effect on elk stress levels, body condition, pregnancy, or herbivory. The ability of free‐living animals to adaptively allocate habitat use across periods of high and low predator activity within the diel cycle is an underappreciated aspect of animal behavior that helps explain why strong antipredator responses may trigger weak ecological effects, and why an LOF may have less conceptual and practical importance than direct killing.

Yellowstone National Park↗

Full annual cycle climate change vulnerability assessment for migratory birds

Climate change is a serious challenge faced by all plant and animal species. Climate change vulnerability assessments (CCVAs) are one method to assess risk and are increasingly used as a tool to inform management plans. Migratory animals move across regions and continents during their annual cycles where they are exposed to diverse climatic conditions. Climate change during any period and in any region of the annual cycle could influence survival, reproduction, or the cues used to optimize timing of migration. Therefore, CCVAs for migratory animals best estimate risk when they include climate exposure during the entire annual cycle. We developed a CCVA incorporating the full annual cycle and applied this method to 46 species of migratory birds breeding in the Upper Midwest and Great Lakes (UMGL) region of the United States. Our methodology included background risk, climate change exposure × climate sensitivity, adaptive capacity to climate change, and indirect effects of climate change. We compiled information about migratory connectivity between breeding and stationary non-breeding areas using literature searches and U.S. Geological Survey banding and re-encounter data. Climate change exposure (temperature and moisture) was assessed using UMGL breeding season climate and winter climate from non-breeding regions for each species. Where possible, we focused on non-breeding regions known to be linked through migratory connectivity. We ranked 10 species as highly vulnerable to climate change and two as having low vulnerability. The remaining 34 species were ranked as moderately vulnerable. In general, including non-breeding data provided more robust results that were highly individualistic by species. Two species were found to be highly vulnerable throughout their annual cycle. Projected drying will have the greatest effect during the non-breeding season for species overwintering in Mexico and the Caribbean. Projected temperature increases will have the greatest effect during the breeding season in UMGL as well as during the non-breeding season for species overwintering in South America. We provide a model for adaptive management of migratory animals in the face of projected climate change, including identification of priority species, research needs, and regions within non-breeding ranges for potential conservation partnerships.

Ecological Applications↗

Resource availability and heterogeneity affect space use and resource selection of a feral ungulate

Animals adjust their habitat use patterns in response to changes in their physiological needs and environmental conditions. Understanding the mechanisms underlying resource selection and space use across time and space reveals effects of the environment on animals' decisions. We explored the effects of habitat availability and heterogeneity on the seasonal and annual space use and resource selection of two free-roaming feral burro ( Equus asinus ) populations in the United States within distinct climate and habitat conditions: the Sonoran Desert and the Colorado Plateau. As an introduced yet protected species in the United States, understanding burros' interactions with habitat elements is important for their conservation and management, as well as the conservation of sympatric wildlife. We used GPS locations of female burros (72 animals across both study areas) to delineate annual and seasonal ranges and resource selection patterns. We evaluated effects of mean and CV of habitat covariates, including forage, distance to water, and topography, representing availability and heterogeneity of resources, on seasonal and annual range size of burros. Moreover, we explored how burro seasonal and annual resource selection patterns were affected by availability and heterogeneity of resources. In the Sonoran Desert study area, burros had smaller seasonal and annual ranges and constant resource selection patterns across a year, likely due to a freshwater lake in the area, making water a nonlimiting resource. Human presence was the greatest factor affecting range size and resource selection in the Sonoran Desert, where burros selected for areas near roads and human recreation. In the Colorado Plateau study area, where resources were more seasonal, we found larger range sizes and fluctuating resource selection patterns compared to the Sonoran Desert population. Spatial variation in forage, water, and topography significantly affected range size of burros inhabiting the Colorado Plateau study area. Productive habitats with available water support smaller ranges and a more consistent pattern of resource selection. Our results highlight the positive effect of habitat heterogeneity and the negative effect of habitat productivity on range size of animals. Our findings contribute to an improved understanding of habitat requirements for free-roaming burros that currently live under various climate and habitat conditions globally.

Arizona, Utah↗

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids ( Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

Ecology↗

Cortisol receptor blockade and seawater adaptation in the euryhaline teleost Fundulus heteroclitus

To examine the role of cortisol in seawater osmoregulation in a euryhaline teleost, adult killifish were acclimated to brackish water (10???) and RU486 or vehicle was administered orally in peanut oil daily for five days at low (40 mg.kg-1) or high dose (200 mg.kg-1). Fish were transferred to 1.5 x seawater (45???) or to brackish water (control) and sampled at 24 h and 48 h after transfer, when Cl- secretion is upregulated. At 24 h, opercular membrane Cl- secretion rate, as Isc, was increased only in the high dose RU486 group. Stimulation of membranes by 3-isobutyl-1-methylxanthine and cAMP increased Isc in vehicle treated controls but those from RU486-treated animals were unchanged and membranes from brackish water animals showed a decrease in Isc. At 48 h, Isc increased and transepithelial resistance decreased in vehicle and RU486 groups, compared to brackish water controls. Plasma cortisol increased in all groups transferred to high salinity, compared to brackish water controls. RU486 treated animals had higher cortisol levels compared to vehicle controls. Vehicle treated controls had lower cortisol levels than untreated or RU486 treated animals, higher stimulation of Isc, and lower hematocrit at 24 h, beneficial effects attributed to increased caloric intake from the peanut oil vehicle. Chloride cell density was significantly increased in the high dose RU486 group at 48 hours, yet Isc was unchanged, suggesting a decrease in Cl- secretion per cell. Thus cortisol enhances NaCl secretion capacity in chloride cells, likely via glucocorticoid type receptors. ?? 2005 Wiley-Liss, Inc.

Journal of Experimental Zoology Part A: Comparativ↗

Detection probability in aerial surveys of feral horses

Observation bias pervades data collected during aerial surveys of large animals, and although some sources can be mitigated with informed planning, others must be addressed using valid sampling techniques that carefully model detection probability. Nonetheless, aerial surveys are frequently employed to count large mammals without applying such methods to account for heterogeneity in visibility of animal groups on the landscape. This often leaves managers and interest groups at odds over decisions that are not adequately informed. I analyzed detection of feral horse (Equus caballus) groups by dual independent observers from 24 fixed-wing and 16 helicopter flights using mixed-effect logistic regression models to investigate potential sources of observation bias. I accounted for observer skill, population location, and aircraft type in the model structure and analyzed the effects of group size, sun effect (position related to observer), vegetation type, topography, cloud cover, percent snow cover, and observer fatigue on detection of horse groups. The most important model-averaged effects for both fixed-wing and helicopter surveys included group size (fixed-wing: odds ratio = 0.891, 95% CI = 0.850–0.935; helicopter: odds ratio = 0.640, 95% CI = 0.587–0.698) and sun effect (fixed-wing: odds ratio = 0.632, 95% CI = 0.350–1.141; helicopter: odds ratio = 0.194, 95% CI = 0.080–0.470). Observer fatigue was also an important effect in the best model for helicopter surveys, with detection probability declining after 3 hr of survey time (odds ratio = 0.278, 95% CI = 0.144–0.537). Biases arising from sun effect and observer fatigue can be mitigated by pre-flight survey design. Other sources of bias, such as those arising from group size, topography, and vegetation can only be addressed by employing valid sampling techniques such as double sampling, mark–resight (batch-marked animals), mark–recapture (uniquely marked and identifiable animals), sightability bias correction models, and line transect distance sampling; however, some of these techniques may still only partially correct for negative observation biases.

Journal of Wildlife Management↗

Using grazing to manage herbaceous structure for a heterogeneity-dependent bird

Grazing management recommendations often sacrifice the intrinsic heterogeneity of grasslands by prescribing uniform grazing distributions through smaller pastures, increased stocking densities, and reduced grazing periods. The lack of patch-burn grazing in semi-arid landscapes of the western Great Plains in North America requires alternative grazing management strategies to create and maintain heterogeneity of habitat structure (e.g., animal unit distribution, pasture configuration), but knowledge of their effects on grassland fauna is limited. The lesser prairie-chicken ( Tympanuchus pallidicinctus ), an imperiled, grassland-obligate, native to the southern Great Plains, is an excellent candidate for investigating effects of heterogeneity-based grazing management strategies because it requires diverse microhabitats among life-history stages in a semi-arid landscape. We evaluated influences of heterogeneity-based grazing management strategies on vegetation structure, habitat selection, and nest and adult survival of lesser prairie-chickens in western Kansas, USA. We captured and monitored 116 female lesser prairie-chickens marked with very high frequency (VHF) or global positioning system (GPS) transmitters and collected landscape-scale vegetation and grazing data during 2013–2015. Vegetation structure heterogeneity increased at stocking densities ≤0.26 animal units/ha, where use by nonbreeding female lesser prairie-chickens also increased. Probability of use for nonbreeding lesser prairie-chickens peaked at values of cattle forage use values near 37% and steadily decreased with use ≥40%. Probability of use was positively affected by increasing pasture area. A quadratic relationship existed between growing season deferment and probability of use. We found that 70% of nests were located in grazing units in which grazing pressure was <0.8 animal unit months/ha. Daily nest survival was negatively correlated with grazing pressure. We found no relationship between adult survival and grazing management strategies. Conservation in grasslands expressing flora community composition appropriate for lesser prairie-chickens can maintain appropriate habitat structure heterogeneity through the use of low to moderate stocking densities (<0.26 animal units/ha), greater pasture areas, and site-appropriate deferment periods. Alternative grazing management strategies (e.g., rest-rotation, season-long rest) may be appropriate in grasslands requiring greater heterogeneity or during intensive drought. Grazing management favoring habitat heterogeneity instead of uniform grazing distributions will likely be more conducive for preserving lesser prairie-chicken populations and grassland biodiversity.

Kansas↗

Incorporating detection probability into northern Great Plains pronghorn population estimates

Pronghorn ( Antilocapra americana ) abundances commonly are estimated using fixed-wing surveys, but these estimates are likely to be negatively biased because of violations of key assumptions underpinning line-transect methodology. Reducing bias and improving precision of abundance estimates through use of detection probability and mark-resight models may allow for more responsive pronghorn management actions. Given their potential application in population estimation, we evaluated detection probability and mark-resight models for use in estimating pronghorn population abundance. We used logistic regression to quantify probabilities that detecting pronghorn might be influenced by group size, animal activity, percent vegetation, cover type, and topography. We estimated pronghorn population size by study area and year using mixed logit-normal mark-resight (MLNM) models. Pronghorn detection probability increased with group size, animal activity, and percent vegetation; overall detection probability was 0.639 (95% CI = 0.612–0.667) with 396 of 620 pronghorn groups detected. Despite model selection uncertainty, the best detection probability models were 44% (range = 8–79%) and 180% (range = 139–217%) greater than traditional pronghorn population estimates. Similarly, the best MLNM models were 28% (range = 3–58%) and 147% (range = 124–180%) greater than traditional population estimates. Detection probability of pronghorn was not constant but depended on both intrinsic and extrinsic factors. When pronghorn detection probability is a function of animal group size, animal activity, landscape complexity, and percent vegetation, traditional aerial survey techniques will result in biased pronghorn abundance estimates. Standardizing survey conditions, increasing resighting occasions, or accounting for variation in individual heterogeneity in mark-resight models will increase the accuracy and precision of pronghorn population estimates.

Journal of Wildlife Management↗

An automated device for provoking and capturing wildlife calls

Some animals exhibit call-and-response behaviors that can be exploited to facilitate detection. Traditionally, acoustic surveys that use call-and-respond techniques have required an observer's presence to perform the broadcast, record the response, or both events. This can be labor-intensive and may influence animal behavior and, thus, survey results. We developed an automated acoustic survey device using commercially available hardware (e.g., laptop computer, speaker, microphone) and an author-created (JS) software program ("HOOT") that can be used to survey for any animal that calls. We tested this device to determine 1) deployment longevity, 2) effective sampling area, and 3) ability to detect known packs of gray wolves (Canis lupus) in Idaho, USA. Our device was able to broadcast and record twice daily for 6&ndash;7 days using the internal computer battery and surveyed an area of 3.3&ndash;17.5 km 2 in relatively open habitat depending on the hardware components used. We surveyed for wolves at 2 active rendezvous sites used by closely monitored, radiocollared wolf packs and obtained 4 responses across both packs over 3 days of sampling. We confirmed reproduction in these 2 packs by detecting pup howls aurally from the resulting device recordings. Our device can broadcast and record animal calls and the computer software is freely downloadable. This automated survey device can be used to collect reliable data while reducing the labor costs traditionally associated with acoustic surveys.

Wildlife Society Bulletin↗

Use and environmental occurrence of veterinary pharmaceuticals in the United States

The purpose of this chapter is to familiarise the reader with the range of veterinary pharmaceuticals used in agriculture in the United States and to provide examples of the environmental occurrence of selected veterinary pharmaceuticals. A 1998 survey conducted by the Animal Health Institute (AHI) reported that there were 109 million cattle, 7.5 billion chickens, 92 million swine, and 292 million turkeys in the United States (AHI 2002). In comparison, a 2002 survey conducted by the National Agricultural Statistics Service (NASS) reported 104 million cattle, 8.6 billion chickens, 60 million swine, and 275 million turkeys in the United States (NASS 2002). To increase the efficiency of food production and maintain economic viability, animal agribusinesses began contracting with cooperative farmers, which lead to a proliferation of large animal-feeding operations (AFOs) over the last decade. Because of the close proximity of the large numbers of animals at these facilities and the potential for the rapid spread of disease, use of pharmaceuticals is important to maintain their operations.

Book chapter↗

Metal exposure and effects in voles and small birds near a mining haul road in Cape Krusenstern National Monument, Alaska

Voles and small passerine birds were live-captured near the Delong Mountain Regional Transportation System (DMTS) haul road in Cape Krusenstern National Monument in northwest Alaska to assess metals exposure and sub-lethal biological effects. Similar numbers of animals were captured from a reference site in southern Cape Krusenstern National Monument for comparison. Histopathological examination of selected organs, and analysis of cadmium, lead, and zinc concentrations in liver and blood samples were performed. Voles and small birds captured from near the haul road had about 20 times greater blood and liver lead concentrations and about three times greater cadmium concentrations when compared to those from the reference site, but there were no differences in zinc tissue concentrations. One vole had moderate metastatic mineralization of kidney tissue, otherwise we observed no abnormalities in internal organs or DNA damage in the blood of any of the animals. The affected vole also had the greatest liver and blood Cd concentration, indicating that the lesion might have been caused by Cd exposure. Blood and liver lead concentrations in animals captured near the haul road were below concentrations that have been associated with adverse biological effects in other studies; however, subtle effects resulting from lead exposure, such as the suppression of the activity of certain enzymes, cannot be ruled out for some individual animals. Results from our 2006 reconnaissance-level study indicate that overall, voles and small birds obtained from near the DMTS road in Cape Krusenstern National Monument were not adversely affected by metals exposure; however, because of the small sample size and other uncertainties, continued monitoring of lead and cadmium in terrestrial habitats near the DMTS road is advised.

Alaska↗

Effects of antenna length and material on output power and detection of miniature radio transmitters

The optimal antenna of transmitters used in small aquatic animals is often a compromise between efficient radio wave propagation and effects on animal behavior. Radio transmission efficiency generally increases with diameter and length of the conductor, but increased antenna length or weight can adversely affect animal behavior. We evaluated the effects of changing antenna length and material on the subsequent tag output power, reception, and detection of tagged fish. In a laboratory, we compared the relative signal strengths in water of 150 MHz transmitters over a range of antenna lengths (from 6 to 30 cm) and materials (one weighing about half of the other). The peak relative signal strengths were at 20 and 22 cm, which are approximately one wavelength underwater at the test frequency. The peak relative signal strengths at these lengths were approximately 50% greater than those of 30 cm antennas, a length commonly used in fisheries research. Few significant differences were present in distances for the operator to hear or the telemetry receiver to decode transmitters from a boat-mounted receiving system based on antenna length, but the percent of tagged fish detected passing a hydroelectric dam fitted with an array of receiving systems was significantly greater at the antenna length with peak output power in laboratory tests. This study indicates careful choice of antenna length and material of small transmitters can be used to reduce weight and possible antenna effects on animal behavior, to maximize tag output power and detection, or to balance these factors based on the needs of the application. ?? 2007 Springer Science+Business Media B.V.

Conference Paper↗

Insights into the latent multinomial model through mark-resight data on female grizzly bears with cubs-of-the-year

Mark-resight designs for estimation of population abundance are common and attractive to researchers. However, inference from such designs is very limited when faced with sparse data, either from a low number of marked animals, a low probability of detection, or both. In the Greater Yellowstone Ecosystem, yearly mark-resight data are collected for female grizzly bears with cubs-of-the-year (FCOY), and inference suffers from both limitations. To overcome difficulties due to sparseness, we assume homogeneity in sighting probabilities over 16 years of bi-annual aerial surveys. We model counts of marked and unmarked animals as multinomial random variables, using the capture frequencies of marked animals for inference about the latent multinomial frequencies for unmarked animals. We discuss undesirable behavior of the commonly used discrete uniform prior distribution on the population size parameter and provide OpenBUGS code for fitting such models. The application provides valuable insights into subtleties of implementing Bayesian inference for latent multinomial models. We tie the discussion to our application, though the insights are broadly useful for applications of the latent multinomial model.

Journal of Agricultural, Biological, and Environme↗

Food availability controls seasonal cycle of growth in Macoma balthica (L.) in San Francisco Bay, California

A 2-yr field study of growth in the bivalve Macoma balthica (L.) at four locations in San Francisco Bay, California, U.S., showed that the timing and rate of growth (increase in shell length) were related to food supply. This clam feeds on both planktonic and benthic microalgae, depending on availability. Growth was apparently food-limited during some months, during one year more than the other, and at some locations more than others. Tissue-weight changes were also related to food availability. The heaviest animals were found in that year and at those locations with the highest chl a concentrations. Tissue-weight gains usually coincided with increased shell-growth rate or with reproductive development, although some large animals showed weight gain independent of both of these factors during periods with mid-range chl a levels. Weight losses coincided with spawning or periods of low growth rate, except at one station where, during a period when most animals were reproductively ripe, food concentrations were high, and shell growth was rapid, animals lost weight. This study failed to show a relation between salinity and the timing or rate of change of either shell length or tissue weight. The mild temperatures (10-23 ??C water temperature) of the area studied resulted in no growth inhibition due to low temperature, but there was some indication that the high air temperatures found in these intertidal areas limited growth rates. ?? 1988.

Journal of Experimental Marine Biology and Ecology↗

Genomic selection for low salinity tolerance in the eastern oyster Crassostrea virginica in Louisiana and Chesapeake Bay populations

The use of genomic selection (GS) to improve traits of interest in aquaculture species is growing with the availability of genomic resources for those species. The eastern oyster , Crassostrea virginica , is a major aquaculture product and keystone species along the U.S. mid-Atlantic and Gulf coasts. Populations and production of C. virginica are threatened by several environmental stressors, and in certain coastal regions, episodic low salinity conditions have contributed to mass mortality events. Here we examined the potential for genomic selection to improve tolerance to extreme low salinity (≤ 2) in eastern oysters and report the evaluation of GS models for C. virginica from two regions- Louisiana and Chesapeake Bay. Tissue samples from both mortalities and survivors of the lab-based salinity challenges (salinity 2, 28 °C) were genotyped on the 66 K C. virginica SNP array. We performed a genome wide association study (GWAS) for both challenges and then evaluated the effects of several different parameters on GS prediction accuracy, including model type (GBLUP, Bayesian, and weighted), data filtering, Bayesian modelling parameters, and trait encoding (Gaussian, ordinal, and censored). GWAS revealed a significant region on chromosome 1 in the Chesapeake animals while the Louisiana animals showed only a few significantly associated loci. GS model type had no significant impact on prediction accuracy in the Chesapeake animals, but a large impact in the Louisiana animals. Likewise, prediction accuracy remained consistent in the Chesapeake Bay challenge with as few as 5000 markers, while accuracy in the Louisiana challenge began to decline with fewer than 25,000 markers. This likely reflects the lower relatedness among the Louisiana individuals due to unintended wild overset. Overall, with moderate prediction accuracies (∼0.45–0.55) in both regions, GS shows the potential to improve low salinity tolerance in eastern oysters. This will be beneficial to selective breeding programs and restoration efforts in regions where this trait improves oyster survival.

Louisiana, Maryland, Virginia↗

Elucidating spatially explicit behavioral landscapes in the Willow Flycatcher

Animal resource selection is a complex, hierarchical decision-making process, yet resource selection studies often focus on the presence and absence of an animal rather than the animal's behavior at resource use locations. In this study, we investigate foraging and vocalization resource selection in a population of Willow Flycatchers, Empidonax traillii adastus , using Bayesian spatial generalized linear models. These models produce “behavioral landscapes” in which space use and resource selection is linked through behavior. Radio telemetry locations were collected from 35 adult Willow Flycatchers ( n = 14 males, n = 13 females, and n = 8 unknown sex) over the 2003 and 2004 breeding seasons at Fish Creek, Utah. Results from the 2-stage modeling approach showed that habitat type, perch position, and distance from the arithmetic mean of the home range (in males) or nest site (in females) were important factors influencing foraging and vocalization resource selection. Parameter estimates from the individual-level models indicated high intraspecific variation in the use of the various habitat types and perch heights for foraging and vocalization. On the population level, Willow Flycatchers selected riparian habitat over other habitat types for vocalizing but used multiple habitat types for foraging including mountain shrub, young riparian, and upland forest. Mapping of observed and predicted foraging and vocalization resource selection indicated that the behavior often occurred in disparate areas of the home range. This suggests that multiple core areas may exist in the home ranges of individual flycatchers, and demonstrates that the behavioral landscape modeling approach can be applied to identify spatially and behaviorally distinct core areas. The behavioral landscape approach is applicable to a wide range of animal taxa and can be used to improve our understanding of the spatial context of behavior and resource selection.

Utah↗

Linking resource selection and mortality modeling for population estimation of mountain lions in Montana

To be most effective, the scale of wildlife management practices should match the range of a particular species&rsquo; movements. For this reason, combined with our inability to rigorously or regularly census mountain lion populations, several authors have suggested that mountain lions be managed in a source-sink or metapopulation framework. We used a combination of resource selection functions, mortality estimation, and dispersal modeling to estimate cougar population levels in Montana statewide and potential population level effects of planned harvest levels. Between 1980 and 2012, 236 independent mountain lions were collared and monitored for research in Montana. From these data we used 18,695 GPS locations collected during winter from 85 animals to develop a resource selection function (RSF), and 11,726 VHF and GPS locations from 142 animals along with the locations of 6343 mountain lions harvested from 1988&ndash;2011 to validate the RSF model. Our RSF model validated well in all portions of the State, although it appeared to perform better in Montana Fish, Wildlife and Parks (MFWP) Regions 1, 2, 4 and 6, than in Regions 3, 5, and 7. Our mean RSF based population estimate for the total population (kittens, juveniles, and adults) of mountain lions in Montana in 2005 was 3926, with almost 25% of the entire population in MFWP Region 1. Estimates based on a high and low reference population estimates produce a possible range of 2784 to 5156 mountain lions statewide. Based on a range of possible survival rates we estimated the mountain lion population in Montana to be stable to slightly increasing between 2005 and 2010 with lambda ranging from 0.999 (SD = 0.05) to 1.02 (SD = 0.03). We believe these population growth rates to be a conservative estimate of true population growth. Our model suggests that proposed changes to female harvest quotas for 2013&ndash;2015 will result in an annual statewide population decline of 3% and shows that, due to reduced dispersal, changes to harvest in one management unit may affect population growth in neighboring units where smaller or even no changes were made. Uncertainty regarding dispersal levels and initial population density may have a significant effect on predictions at a management unit scale (i.e. 2000 km 2 ), while at a regional scale (i.e. 50,000 km 2 ) large differences in initial population density result in relatively small changes in population growth rate, and uncertainty about dispersal may not be as influential. Doubling the presumed initial density from a low estimation of 2.19 total animals per 100 km 2 resulted in a difference in annual population growth rate of only 2.6% statewide when compared to high density of 4.04 total animals per 100 km 2 (low initial population estimate &lambda; = 0.99, while high initial population estimate &lambda; = 1.03). We suggest modeling tools such as this may be useful in harvest planning at a regional and statewide level.

Ecological Modelling↗