scholarly journals spaceNtime: an R package for estimating abundance of unmarked animals using camera-trap photographs

2021 ◽  
Author(s):  
Anna K. Moeller ◽  
Paul M. Lukacs
Keyword(s):  
R Package ◽  
Camera Trap ◽  
Estimation Methods ◽  
Sampling Effort ◽  
Target Species ◽  
Time To Event ◽  
Independent Events ◽  
Level Of Knowledge ◽  
Instantaneous Sampling ◽  
Event Models

AbstractThe space to event (STE), time to event (TTE), and instantaneous sampling (IS) methods were developed to estimate abundance of unmarked animals from camera trap images (Moeller et al. in Ecosphere 9(8):e02331, 2018). The space and time to event models use camera data in a different way than other abundance estimation methods do. Instead of using counts of animals over independent events, STE uses a measure of sampled space before the first detection of the target species, and TTE uses the time until the first detection. We introduce , a free and open-source R package designed to assist in the implementation of the STE and TTE models, along with the IS estimator. This package takes the user through the steps of transforming data, defining sampling effort, selecting sampling occasions, building encounter histories, and estimating abundance from camera data using these three methods. The package is designed for users with a baseline level of knowledge of R and statistics, without requiring expertise in either.

Fishing Cat Prionailurus viverrinus Bennett, 1833 (Carnivora: Felidae) distribution and habitat characteristics in Chitwan National Park, Nepal

2018 ◽  
Vol 10 (11) ◽  
pp. 12451-12458 ◽  
Author(s):  
Rama Mishra ◽  
Khadga Basnet ◽  
Rajan Amin ◽  
Babu Ram Lamichhane
Keyword(s):  
National Park ◽  
Buffer Zone ◽  
Camera Trap ◽  
Habitat Characteristics ◽  
Oxbow Lakes ◽  
River Floodplains ◽  
Independent Events ◽  
Awareness Programs ◽  
Chitwan National Park ◽  
Threaten Species

The Fishing Cat is a highly specialized and threatened felid, and its status is poorly known in the Terai region of Nepal.  Systematic camera-trap surveys, comprising 868 camera-trap days in four survey blocks of 40km2 in Rapti, Reu and Narayani river floodplains of Chitwan National Park, were used to determine the distribution and habitat characteristics of this species.  A total of 19 photographs of five individual cats were recorded at three locations in six independent events.  Eleven camera-trap records obtained during surveys in 2010, 2012 and 2013 were used to map the species distribution inside Chitwan National Park and its buffer zone.  Habitat characteristics were described at six locations where cats were photographed.  The majority of records were obtained in tall grassland surrounding oxbow lakes and riverbanks.  Wetland shrinkage, prey (fish) depletion in natural wetlands and persecution threaten species persistence.  Wetland restoration, reducing human pressure and increasing fish densities in the wetlands, provision of compensation for loss from Fishing Cats and awareness programs should be conducted to ensure their survival.  We also recommend studying genetic diversity of sub-populations, as well as habitat use by radio-tagging. 

A comparison of estimators to evaluate the discriminatory power of time-to-event models

2012 ◽  
Vol 31 (23) ◽  
pp. 2588-2609 ◽  
Author(s):  
Matthias Schmid ◽  
Sergej Potapov
Keyword(s):  
Discriminatory Power ◽  
Time To Event ◽  
Event Models

scholarly journals Quantifying the predictive accuracy of time-to-event models in the presence of competing risks

2011 ◽  
Vol 53 (1) ◽  
pp. 88-112 ◽  
Author(s):  
Rotraut Schoop ◽  
Jan Beyersmann ◽  
Martin Schumacher ◽  
Harald Binder
Keyword(s):  
Competing Risks ◽  
Predictive Accuracy ◽  
Time To Event ◽  
Event Models

scholarly journals Semiparametric regression for discrete time-to-event data

2018 ◽  
Vol 18 (3-4) ◽  
pp. 322-345 ◽  
Author(s):  
Moritz Berger ◽  
Matthias Schmid
Keyword(s):  
Semiparametric Regression ◽  
Outcome Variable ◽  
Nonlinear Functions ◽  
Time To Event ◽  
Regression Methods ◽  
Time To Event Data ◽  
Duration Of Unemployment ◽  
Event Models ◽  
Analyse Data ◽  
Event Times

Abstract: Time-to-event models are a popular tool to analyse data where the outcome variable is the time to the occurrence of a specific event of interest. Here, we focus on the analysis of time-to-event outcomes that are either intrinsically discrete or grouped versions of continuous event times. In the literature, there exists a variety of regression methods for such data. This tutorial provides an introduction to how these models can be applied using open source statistical software. In particular, we consider semiparametric extensions comprising the use of smooth nonlinear functions and tree-based methods. All methods are illustrated by data on the duration of unemployment of US citizens.

scholarly journals Hydrothermal-time-to-event models for seed germination

2018 ◽  
Vol 101 ◽  
pp. 129-139 ◽  
Author(s):  
Andrea Onofri ◽  
Paolo Benincasa ◽  
Mohsen B. Mesgaran ◽  
Christian Ritz
Keyword(s):  
Seed Germination ◽  
Hydrothermal Time ◽  
Time To Event ◽  
Event Models

scholarly journals MiRKAT: kernel machine regression-based global association tests for the microbiome

2020 ◽  
Author(s):  
Nehemiah Wilson ◽  
Ni Zhao ◽  
Xiang Zhan ◽  
Hyunwook Koh ◽  
Weijia Fu ◽  
...  
Keyword(s):  
R Package ◽  
Effect Sizes ◽  
Supplementary Information ◽  
Time To Event ◽  
Kernel Machine ◽  
Association Testing ◽  
Higher Power ◽  
Kernel Machine Regression ◽  
Two Measures ◽  
Rv Coefficient

Abstract Summary Distance-based tests of microbiome beta diversity are an integral part of many microbiome analyses. MiRKAT enables distance-based association testing with a wide variety of outcome types, including continuous, binary, censored time-to-event, multivariate, correlated and high-dimensional outcomes. Omnibus tests allow simultaneous consideration of multiple distance and dissimilarity measures, providing higher power across a range of simulation scenarios. Two measures of effect size, a modified R-squared coefficient and a kernel RV coefficient, are incorporated to allow comparison of effect sizes across multiple kernels. Availability and implementation MiRKAT is available on CRAN as an R package. Supplementary information Supplementary data are available at Bioinformatics online.

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