Distiller et al., 2020 - Google Patents
Using Continuous‐Time Spatial Capture–Recapture models to make inference about animal activity patternsDistiller et al., 2020
View PDF- Document ID
- 1343070468844423585
- Author
- Distiller G
- Borchers D
- Foster R
- Harmsen B
- Publication year
- Publication venue
- Ecology and Evolution
External Links
Snippet
Quantifying the distribution of daily activity is an important component of behavioral ecology. Historically, it has been difficult to obtain data on activity patterns, especially for elusive species. However, the development of affordable camera traps and their widespread usage …
- 230000000694 effects 0 title abstract description 68
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce, e.g. shopping or e-commerce
- G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
- G06Q30/0202—Market predictions or demand forecasting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
Similar Documents
Publication | Publication Date | Title |
---|---|---|
O’Connor et al. | Camera trap arrays improve detection probability of wildlife: Investigating study design considerations using an empirical dataset | |
De Palma et al. | Ecological traits affect the sensitivity of bees to land‐use pressures in E uropean agricultural landscapes | |
Abrahms et al. | Does wildlife resource selection accurately inform corridor conservation? | |
Frederiksen et al. | The demographic impact of extreme events: stochastic weather drives survival and population dynamics in a long‐lived seabird | |
Rowcliffe et al. | Quantifying levels of animal activity using camera trap data | |
Fragoso et al. | Line transect surveys underdetect terrestrial mammals: implications for the sustainability of subsistence hunting | |
Lynch et al. | Spatially integrated assessment reveals widespread changes in penguin populations on the Antarctic Peninsula | |
Saunders et al. | Disentangling data discrepancies with integrated population models | |
Ramsey et al. | Estimating population density from presence–absence data using a spatially explicit model | |
Pease et al. | Single-camera trap survey designs miss detections: impacts on estimates of occupancy and community metrics | |
Thompson et al. | A framework for inference about carnivore density from unstructured spatial sampling of scat using detector dogs | |
Distiller et al. | Using Continuous‐Time Spatial Capture–Recapture models to make inference about animal activity patterns | |
Jennelle et al. | State‐specific detection probabilities and disease prevalence | |
Royle et al. | Hierarchical spatial capture–recapture models: modelling population density in stratified populations | |
Olea et al. | Spatially explicit estimation of occupancy, detection probability and survey effort needed to inform conservation planning | |
Fourcade et al. | Temperature drives abundance fluctuations, but spatial dynamics is constrained by landscape configuration: Implications for climate‐driven range shift in a butterfly | |
Walker et al. | Distribution of duck broods relative to habitat characteristics in the Prairie Pothole Region | |
Oedekoven et al. | Improving distance sampling: accounting for covariates and non‐independency between sampled sites | |
Matechou et al. | Monitoring abundance and phenology in (multivoltine) butterfly species: a novel mixture model | |
Fidino et al. | Effect of lure on detecting mammals with camera traps | |
Chandler et al. | Estimating recruitment from capture–recapture data by modelling spatio‐temporal variation in birth and age‐specific survival rates | |
Davis et al. | Beyond climate envelope projections: Roe deer survival and environmental change | |
Nuno et al. | Matching observations and reality: using simulation models to improve monitoring under uncertainty in the S erengeti | |
Fidino et al. | Using Fourier series to estimate periodic patterns in dynamic occupancy models | |
Péron et al. | Estimating nest abundance while accounting for time‐to‐event processes and imperfect detection |