Publications by authors named "James D Nichols"

Athletic performance data are modeled in an effort to better understand the relationship between both hours spent training and a measurement of "commitment" to that training, and improvements in performance. Both increased training time and greater commitment were predicted to produce larger increases in performance improvement, and commitment was predicted to be the more important determinant of improvement. The performance of 108 soccer players (ages 9-18) was quantified over a 10-week training program.

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We conducted a range-wide investigation of the dynamics of site-level reproductive rate of northern spotted owls using survey data from 11 study areas across the subspecies geographic range collected during 1993-2018. Our analytical approach accounted for imperfect detection of owl pairs and misclassification of successful reproduction (i.e.

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Stay-at-home orders and shutdowns of non-essential businesses are powerful, but socially costly, tools to control the pandemic spread of SARS-CoV-2. Mass testing strategies, which rely on widely administered frequent and rapid diagnostics to identify and isolate infected individuals, could be a potentially less disruptive management strategy, particularly where vaccine access is limited. In this paper, we assess the extent to which mass testing and isolation strategies can reduce reliance on socially costly non-pharmaceutical interventions, such as distancing and shutdowns.

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Article Synopsis
  • Invasive species, like the barred owl, can cause big problems for native animals, such as the northern spotted owl, by competing for food and space.
  • A study showed that when barred owls were removed, the northern spotted owls did better, with more surviving and moving around.
  • The northern spotted owl population started to stabilize in areas where barred owls were taken out, but it continued to decline in places where they were still present.
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Poaching is a pervasive threat to wildlife, yet quantifying the direct effect of poaching on wildlife is rarely possible because both wildlife and threat data are infrequently collected concurrently. In this study, we used poaching data collected through the Management Information System (MIST) and wildlife camera trap data collected by the Tropical Ecology Assessment and Monitoring (TEAM) network from 2014 to 2017 in Volcanoes National Park, Rwanda. We implemented co-occurrence multi-season occupancy models that accounted for imperfect detection to investigate the effect of poaching on initial occupancy, colonization, and extinction of five mammal species.

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More than 1.6 million Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) tests were administered daily in the United States at the peak of the epidemic, with a significant focus on individual treatment. Here, we show that objective-driven, strategic sampling designs and analyses can maximize information gain at the population level, which is necessary to increase situational awareness and predict, prepare for, and respond to a pandemic, while also continuing to inform individual treatment.

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Many published studies in ecological science are viewed as stand-alone investigations that purport to provide new insights into how ecological systems behave based on single analyses. But it is rare for results of single studies to provide definitive results, as evidenced in current discussions of the "reproducibility crisis" in science. The key step in science is the comparison of hypothesis-based predictions with observations, where the predictions are typically generated by hypothesis-specific models.

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Understanding the relative impact of climate change and land cover change on changes in avian distribution has implications for the future course of avian distributions and appropriate management strategies. Due to the dynamic nature of climate change, our goal was to investigate the processes that shape species distributions, rather than the current distributional patterns. To this end, we analyzed changes in the distribution of Eastern Wood Pewees () and Red-eyed Vireos () from 1997 to 2012 using Breeding Bird Survey data and dynamic correlated-detection occupancy models.

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Disentangling the role of competition in regulating the distribution of sympatric species can be difficult because species can have different habitat preferences or time use that introduce non-random patterns that are not related to interspecific interactions. We adopted a multi-step approach to systematically incorporate habitat preferences while investigating the co-occurrence of two presumed competitors, morphologically similar, and closely related ground-dwelling birds: the brown tinamou (Crypturellus obsoletus) and the tataupa tinamou (C. tataupa).

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Small felids influence ecosystem dynamics through prey and plant population changes. Although most of these species are threatened, they are accorded one of the lowest research efforts of all felids, and we lack basic information about them. Many felids occur in sympatry, where intraguild competition is frequent.

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Markov decision processes (MDPs), which involve a temporal sequence of actions conditioned on the state of the managed system, are increasingly being applied in natural resource management. This study focuses on the modification of a traditional MDP to account for those cases in which an action must be chosen after a significant time lag in observing system state, but just prior to a new observation. In order to calculate an optimal decision policy under these conditions, possible actions must be conditioned on the previous observed system state and action taken.

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There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data.

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Monitoring is best viewed as a component of some larger programme focused on science or conservation. The value of monitoring is determined by the extent to which it informs the parent process. Animal translocation programmes are typically designed to augment or establish viable animal populations without changing the local community in any detrimental way.

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The occurrence of false positive detections in presence-absence data, even when they occur infrequently, can lead to severe bias when estimating species occupancy patterns. Building upon previous efforts to account for this source of observational error, we established a general framework to model false positives in occupancy studies and extend existing modeling approaches to encompass a broader range of sampling designs. Specifically, we identified three common sampling designs that are likely to cover most scenarios encountered by researchers.

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Ecologists frequently try to predict the future geographic distributions of species. Most studies assume that the current distribution of a species reflects its environmental requirements (i.e.

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Crop and livestock depredation by wildlife is a primary driver of human-wildlife conflict, a problem that threatens the coexistence of people and wildlife globally. Understanding mechanisms that underlie depredation patterns holds the key to mitigating conflicts across time and space. However, most studies do not consider imperfect detection and reporting of conflicts, which may lead to incorrect inference regarding its spatiotemporal drivers.

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The role of competition in structuring biotic communities at fine spatial scales is well known from detailed process-based studies. Our understanding of competition's importance at broader scales is less resolved and mainly based on static species distribution maps. Here, we bridge this gap by examining the joint occupancy dynamics of an invading species (Barred Owl, Strix varia) and a resident species (Northern Spotted Owl, Strix occidentalis caurina) in a 1000-km study area over a 22-year period.

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In this article, we first extend the superpopulation capture-recapture model to multiple states (locations or populations) for two age groups., Wen et al., (2011; 2013) developed a new approach combining capture-recapture data with population assignment information to estimate the relative contributions of in situ births and immigrants to the growth of a single study population.

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Large-scale biodiversity data are needed to predict species' responses to global change and to address basic questions in macroecology. While such data are increasingly becoming available, their analysis is challenging because of the typically large heterogeneity in spatial sampling intensity and the need to account for observation processes. Two further challenges are accounting for spatial effects that are not explained by covariates, and drawing inference on dynamics at these large spatial scales.

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Although many taxa have declined globally, conservation actions are inherently local. Ecosystems degrade even in protected areas, and maintaining natural systems in a desired condition may require active management. Implementing management decisions under uncertainty requires a logical and transparent process to identify objectives, develop management actions, formulate system models to link actions with objectives, monitor to reduce uncertainty and identify system state (i.

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Many species are found today in the form of fragmented populations occupying patches of remnant habitat in human-altered landscapes. The persistence of these population networks requires a balance between extinction and colonization events assumed to be primarily related to patch area and isolation, but the contribution of factors such as the characteristics of patch and matrix habitats, the species' traits (habitat specialization and dispersal capabilities) and variation in climatic conditions have seldom been evaluated simultaneously. The identification of environmental variables associated with patch occupancy and turnover may be especially useful to enhance the persistence of multiple species under current global change.

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Large-scale presence-absence monitoring programs have great promise for many conservation applications. Their value can be limited by potential incorrect inferences owing to observational errors, especially when data are collected by the public. To combat this, previous analytical methods have focused on addressing non-detection from public survey data.

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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.

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This work describes several approaches to the estimation of target detection and identification probabilities as a function of target range. A Bayesian approach to estimation is adopted, whereby the posterior probability distributions associated with these probabilities are analytically derived. The parameter posteriors are then used to develop credible intervals quantifying the degree of uncertainty in the parameter estimates.

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