Browsing by Subject "abundance"
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Item Arctic Peregrine Falcon Abundance on Cliffs Along the Colville River, Alaska, 1981-2002 and Covariate Input Files(2015-04-15) Bruggeman, Jason E.; Swem, Ted; Andersen, David E; Kennedy, Patricia L.; Nigro, Debora; brug0006@umn.edu; Bruggeman, Jason E.Arctic peregrine falcons (Falco peregrinus tundrius; hereafter Arctic peregrine) have a limited and northern breeding distribution, including the Colville River Special Area (CRSA) in the National Petroleum Reserve-Alaska, USA. We quantified influences of climate, topography, nest productivity, prey habitat, density dependence, and interspecific competition affecting Arctic peregrines in the CRSA by applying the Dail-Madsen model to estimate abundance and vital rates of adults on nesting cliffs from 1981 through 2002. Arctic peregrine abundance increased throughout the 1980s, which spanned the population's recovery from DDT-induced reproductive failure, until exhibiting a stationary trend in the 1990s. Apparent survival rate (i.e., emigration; death) was negatively correlated with number of adult Arctic peregrines on the cliff the previous year, suggesting effects of density-dependent population regulation. Apparent survival rate and arrival rate (i.e., immigration; recruitment) were higher during years with earlier snowmelt and milder winters, and apparent survival was positively correlated with nesting season maximum daily temperature. Arrival rate was positively correlated with average Arctic peregrine productivity along a cliff segment from the previous year and initial abundance was positively correlated with cliff height. Higher cliffs with documented higher productivity, and presumably indicative of higher quality habitat, are a priority for continued protection from potential nearby development and disturbance to minimize population-level impacts. Our work provides insight into factors affecting a population during and after recovery, and demonstrates how the Dail-Madsen model can be used for any unmarked population with multiple years of abundance data collected through repeated surveys.Item Bird Point Counts from Downtown Minneapolis During the 2016 Breeding Season(2018-11-15) Anderson, Abigail W; awoodsanderson at g m a i l (dot) com; Anderson, Abigail WThese data document species richness and abundance of the local breeding bird community in downtown Minneapolis, Minnesota. I used a conventional point count methodology (Bibby et al. 2000) to sample a total of 16 locations (or transect areas) all with a 50-meter radius. All observation periods took place between 1 June and 5 July 2016. The data can be used to derive species abundance indices and bird density. Furthermore, the data contain elements that permit more sophisticated statistical modeling such as time-depletion (removal) or distance sampling techniques.Item Post-Fire Associations Of Butterfly Behavior, Occupancy, And Abundance With Environmental Variables And Nectar Sources In The Sierra Nevada, California(2015-12) Pavlik, DavidFire can alter the quality of habitat for butterflies. Fire also affects environmental attributes associated with the distribution, abundance, and reproduction of butterflies. The effects of fire on butterfly occupancy, and on environmental attributes that are associated with butterfly occupancy, are largely unknown. In 2014 and 2015, we conducted butterfly and vegetation surveys within the Rim Fire boundary in California. We analyzed sugar and sucrose masses, and proportion of sucrose, in 20 nectar sources. We found no evidence that intensity of use was associated with sugar mass, mass of sucrose, or the relative proportion of sucrose. We found that environmental attributes associated with occupancy of some species were also associated with the abundances of those species. Burn severity affected environmental attributes that were associated with butterfly occupancy and abundance. Understanding how fire affects environmental attributes associated with occupancy and abundance can inform use of prescribed fire or management following wildfire.Item R code and output supporting: Time series sightability modeling of animal populations(2017-03-29) ArchMiller, Althea A; Fieberg, John R; Dorazio, Robert M; St. Clair, Katherine; althea.archmiller@gmail.com; ArchMiller, Althea AThe goal of our study was to expand a previously developed model-based approach to include random effects and a temporal spline for time series modeling of multiple years of operational survey data. We developed a Bayesian hierarchical model as our framework to build and compare fixed-effects and temporal model-based sightability models applied to 12 years of MN moose operational survey data. Here, we share the Program R code and data necessary to replicate the manuscript results that demonstrate how our time series sightability modeling approach can increase the precision of population estimators and predict population dynamics with smoother (and thus more realistic trends) through time.Item Simulating Effects of Imperfect Detectability in Bird Surveys(2016-11) Rigby, ElizabethCounts obtained from point count bird surveys can be treated as an index to bird abundance, but imperfect detectability can complicate inferences about abundance. Adjustment analysis methods, including double-observer, replicated counts, removal, and distance sampling methods, have been developed to estimate detection in addition to abundance. These methods require additional information to estimate detection, which may entail added logistical costs or be additional sources of error. It is not clear when or if adjustment methods outperform index methods, or how the benefits of adjustment methods compare to their costs. I simulated point counts of birds, modeling birds spatially as moving within bivariate normal territories, modeling song production as an autocorrelated process, and modeling perceptibility as a logit function of distance to the observer. In Chapter 1, I simulated counts using a test scenario with parameters reflecting surveys of black-throated blue warblers (BTBW, Setophaga caerulescens), analyzed counts using index and adjustment analysis methods, then evaluated and compared the performance of analysis methods. Estimates from index methods underestimated true density of birds (Dp) for all survey types, but were highly correlated with true density. Adjusted estimates from distance sampling and removal analysis methods showed a reduction in bias as compared to index estimates, but had reduced correlation with true density. Adjusted estimates from double-observer analysis methods were nearly unchanged from index estimates. Adjusted estimates from replicated counts analysis methods were susceptible to highly inflated density estimates, resulting in extremely high bias and low correlation with true density. Index methods, while biased, were better correlated with true density and would provide better information about changes in abundance than an adjustment analysis method for the BTBW scenario. If detection is constant and relative abundance is sufficient to meet survey objectives, using an index method is often preferable. For systems with variable detection probability where inference about absolute abundance is necessary to meet objectives, practitioners should select adjustment methods suited to model the source of imperfect detection in their system. Ill-suited adjustment methods will not improve inference and are no more useful than an index. In Chapter 2, I used the model to simulate counts for scenarios with high or low availability and high or low perceptibility. I also included scenarios where abundance was confounded with perceptibility, and scenarios where they were independent. I then analyzed count data using index methods and adjustment methods. Although index methods were biased and only had a strong correlation with true density when detectability was high, adjustment methods generally did not offer an improvement. As compared to index methods, adjustment method performance ranged from far worse (replicated counts), to no added value (double-observer) to moderate improvement (in bias only, for removal and distance sampling in specific scenarios). Practitioners should carefully consider the sources of variation in detection probability in their system. If detection components are unknown or known to be variable, I advise practitioners to perform a pilot study to estimate detection components. Additionally, practitioners should standardize their methods to increase availability and perceptibility in their surveys and to lower the variation in these detection components. In Chapter 3, I conducted simulated bird surveys using recorded bird songs to assess factors affecting detection probability in grassland bird point counts. I used mixed effects logistic regression models to estimate factors affecting detection probability and to estimate and visualize the variation in the area around the observer where birds can be perceived (the perceptible area). I conducted simulated surveys with 8926 binary opportunities for detection in Minnesota grasslands in 2011 and 2012. Species, distance to the observer, wind speed and direction, observer, and density of vegetation all affected detection of recorded bird songs. Species had a strong effect; the size of the predicted perceptible area around the observer differed by more than 10-fold among species. Wind also had a strong effect on detection. As wind speed increased, probability of detection downwind of the observer was reduced and the perceptible area around the observer became smaller and more asymmetrical. The effective distance at which an observer is more likely to detect a bird than to not detect it may differ among species and angles to the wind, even within the same survey. I recommend using fixed-radius counts for bird surveys in grasslands and reducing the variation in detection probability by standardizing surveys across wind conditions.